Bridge construction material management system based on big data

Abstract

The invention relates to the technical field of construction material management, in particular to a bridge construction material management system based on big data, which comprises a progress deviation analysis module, a material consumption comparison module, an inventory response adjustment module, a logistics optimization decision module and a supply chain evaluation module. According to the invention, through real-time monitoring and data analysis, the bridge construction material management efficiency is improved, the real-time performance and accuracy of material demand prediction and inventory adjustment are improved, and through a big data system, the process progress and the material use condition can be analyzed in real time, the material plan is dynamically adjusted, and the waiting time and waste are reduced, for example, the work efficiency is improved. Material consumption is calculated in real time, demand prediction is updated in real time, it is ensured that material supply is accurately matched with actual demands, excess or insufficient phenomena are reduced, a logistics optimization strategy is directly based on process dependence and emergency demands, the response speed and efficiency of material distribution are improved, and the problems of project delay and high cost are reduced.

Description

Technical Field

[0001] This invention relates to the field of construction material management technology, and in particular to a bridge construction material management system based on big data. Background Technology

[0002] The field of construction material management technology involves the comprehensive management and control of various materials required in the construction process to ensure the smooth progress and efficient execution of the project. It mainly includes all aspects of material procurement, transportation, storage, use, consumption and recycling. As the scale and complexity of construction projects increase, construction material management becomes more complex and important.

[0003] Among them, the big data-based bridge construction material management system is a system that uses big data technology to accurately manage and optimize the scheduling of materials required during bridge construction. By monitoring the usage of construction materials in real time and collecting and analyzing a large amount of construction-related data, it provides more accurate material demand forecasts, inventory management, and procurement plans. Its main purpose is to ensure the timely supply and rational use of materials in bridge construction projects, thereby improving construction efficiency, reducing costs, and minimizing material waste.

[0004] Existing technologies rely on manual recording and periodic updates, resulting in information lag and an inability to effectively respond to rapidly changing on-site needs. This delay leads to a disconnect between material supply plans and actual needs in data updates and decision-making, causing resource waste and construction stagnation. The lack of efficient data analysis and response mechanisms makes it difficult for material management to adjust procurement and inventory strategies in real time. Especially in scenarios involving urgent supply and closely related processes, existing technologies struggle to provide effective solutions, impacting construction progress and management costs. Summary of the Invention

[0005] To address the shortcomings of existing technologies, which rely on manual recording and periodic updates, leading to information lag and an inability to effectively respond to rapidly changing on-site needs, this delay in data updates and decision-making causes a disconnect between material supply plans and actual demand, resulting in resource waste and construction stagnation. The lack of efficient data analysis and response mechanisms makes it difficult to adjust procurement and inventory strategies in real time, especially in scenarios involving urgent supply and closely intertwined processes. Existing technologies struggle to provide effective solutions, impacting construction progress and management costs. This invention provides a bridge construction material management system based on big data. The technical solution is as follows: On the one hand, a bridge construction material management system based on big data is provided, including: The schedule deviation analysis module is based on the construction task of the main girder section of the bridge. It obtains the work procedures, equipment operation time and equipment failure downtime, records the difference between the actual completion time and the planned completion time of each procedure, and identifies the key factors that cause construction delays by comparing the operating efficiency and downtime frequency of the equipment, and obtains the delayed procedure index. The material consumption comparison module analyzes the material usage and worker workload of each process based on the delayed process index. Combined with the data on rebar tying and concrete pouring, it calculates the daily material consumption in real time, determines the amount of additional materials needed, and obtains material shortage analysis data. The inventory response adjustment module analyzes the current inventory status and material outbound frequency based on the material shortage analysis data, calculates whether the inventory level can meet short-term construction needs based on the time it takes to transport materials to the construction site, adjusts the warehouse inventory level, and obtains the inventory adjustment configuration. Based on the aforementioned inventory adjustment configuration, the logistics optimization decision module analyzes the application frequency and criticality of materials in bridge construction, optimizes logistics according to the urgent supply needs of materials and the dependencies between processes, and generates priority delivery indicators.

[0006] On the other hand, the delayed process index includes process number, delay duration, and key influencing factors; the material gap analysis data includes gap material type, gap quantity, and key processes; the inventory adjustment configuration includes adjustment amount and delivery adjustment result; and the priority delivery index includes material type, delivery priority, and dependent processes.

[0007] On the other hand, the schedule deviation analysis module includes: The process time processing submodule is based on the construction task of the main beam section of the bridge. It collects the planned completion time and actual completion time of each process, calculates the time difference, and identifies the time difference with the process number to establish a process time difference marker. Based on the process time difference marker, the equipment operation efficiency submodule analyzes the equipment operation time and actual operation time corresponding to the construction process, calculates the equipment single-period operation efficiency, forms a corresponding sequence of efficiencies according to the process sequence, and performs position matching with the process time difference marker to obtain an efficiency coefficient matching table. The key process screening submodule obtains the equipment failure downtime of each process according to the efficiency coefficient matching table, calculates its proportion in the total working hours, and filters out process numbers with large deviations and low efficiency to obtain the delayed process index.

[0008] On the other hand, the material consumption comparison module includes: The process usage assessment submodule, based on the delayed process index, collects material usage records and worker working hours for the corresponding process. By statistically analyzing the man-hour and material usage within a single process, it compares the data with the historical average usage of the process to identify material usage deviations and obtain the material offset range. The daily consumption calculation submodule analyzes the data of steel bar binding and concrete pouring based on the material offset range, calculates the daily material usage for each process, compares the actual usage with the planned supply, determines the difference between the daily consumption and supply of each material, and obtains a record of the daily consumption difference. The material shortage screening submodule calls the daily consumption difference record to evaluate the degree of material shortage in each process, sorts them from high to low according to the shortage amount, identifies the key processes and material types with insufficient material supply, and obtains material gap analysis data.

[0009] On the other hand, the analysis of rebar tying and concrete pouring data calculates the daily material usage for each process, compares the actual usage with the planned supply, and uses the following formula: ; Determine the first Daily consumption difference of various materials ,in, Representing the Volume requirements in each process Representing the The unit material consumption rate of each process, Representing the The planned supply of this material This represents the total number of processes.

[0010] On the other hand, the inventory response adjustment module includes: The inventory status detection submodule collects the current inventory of materials and recent outbound records based on the material shortage analysis data, counts the outbound frequency of different materials and classifies them by type, compares the ratio of inventory and outbound data, evaluates the circulation speed and consumption rate of each material, and generates an inventory turnover speed index. The transportation time calculation submodule calls the inventory turnover speed index to analyze the transportation path and time of each material from the warehouse to the construction site. Combined with the batch transfer frequency and time cost, it calculates the transportation time. Combined with the inventory data, it evaluates the construction cycle supported by the materials and obtains the transportation support efficiency. The outbound dynamic control submodule analyzes the material shortage data and the current inventory coverage based on the transportation support efficiency, adjusts the material inventory level according to the current demand, matches the changes in construction demand, and obtains the inventory adjustment configuration.

[0011] On the other hand, the analysis of the transportation route and time for each material from the warehouse to the construction site uses the following formula: ; Calculate the total transportation time ,in, Representing the The transportation distance of the materials Representing the The transport speed of this material Representing the Loading and unloading time of various materials The number of representative material types.

[0012] On the other hand, the logistics optimization decision module includes: The delivery priority identification submodule identifies material types with high-frequency delivery needs based on the inventory adjustment configuration, evaluates the frequency of material outbound and usage, matches the construction schedule, determines the types of materials that need to be prioritized for delivery, and obtains a set of high-frequency materials. The material application positioning submodule collects application data of materials in different bridge construction sections based on the high-frequency material set, counts the frequency of material use in the hanging basket section and the side span cast-in-place section, and evaluates its criticality and application scope in the construction process to obtain the material application coverage rate. The supply emergency prioritization submodule calls the material application coverage, analyzes the urgent supply demand of materials and the dependencies between processes, assesses the impact of undelivered materials on upstream processes, prioritizes materials that are critical to construction, and generates priority delivery indicators.

[0013] On the other hand, the system also includes: The supply chain assessment module uses the priority delivery index to check the deviation between the actual material delivery time and the expected delivery time in the supply chain, analyze the material demand and supply time of the hanging basket section and the side span cast-in-place section, quantify the supply time deviation, assess the impact of the deviation on the construction progress, and obtain the material supply analysis results. The material supply analysis results include deviation, impact assessment results, and demand matching degree.

[0014] On the other hand, the supply chain assessment module includes: The delivery time offset submodule uses the priority delivery index to obtain the actual arrival time and scheduled arrival time of related materials. By comparing the time data, it calculates the arrival time deviation of each type of material, evaluates the impact of the deviation on supply chain efficiency, and obtains the delivery deviation area. Based on the delivery deviation area, the demand process matching submodule analyzes the matching between the material usage time and supply time of the hanging basket section and the side span cast-in-place section, evaluates the time coordination between material supply and actual demand, determines whether the material supply is synchronized with the process demand, and obtains the process synchronization efficiency. The schedule impact assessment submodule analyzes the process delays caused by material supply delays based on the process synchronization efficiency, assesses the potential impact of the delays on the construction project schedule, quantifies the degree of impact, optimizes future material supply and process arrangement, and obtains material supply analysis results.

[0015] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: Real-time monitoring and data analysis have improved the efficiency of bridge construction material management, enhanced the timeliness and accuracy of material demand forecasting and inventory adjustments, and enabled real-time analysis of process progress and material usage through big data systems. This allows for dynamic adjustments to material plans, reducing waiting time and waste. For example, real-time calculation of material consumption and instant updates to demand forecasts ensure that material supply accurately matches actual needs, reducing surpluses or shortages. Logistics optimization strategies are directly based on process dependencies and urgent needs, improving the response speed and efficiency of material delivery and reducing project delays and cost overruns. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the system of the present invention; Figure 2 This is a schematic diagram of the system framework of the present invention; Figure 3 This is a flowchart of the schedule deviation analysis module of the present invention; Figure 4 This is a flowchart of the material consumption comparison module of the present invention; Figure 5 This is a flowchart of the inventory response adjustment module of the present invention; Figure 6 This is a flowchart of the logistics optimization decision module of the present invention; Figure 7 This is a flowchart of the supply chain assessment module of the present invention. Detailed Implementation

[0018] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0019] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0020] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0021] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0022] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0023] This invention provides a bridge construction material management system based on big data, such as... Figure 1 As shown, the system includes: The schedule deviation analysis module is based on the construction task of the main girder section of the bridge. It obtains the work procedures, equipment operation time and equipment failure downtime, records the difference between the actual completion time and the planned completion time of each procedure, and identifies the key factors that cause construction delays by comparing the operating efficiency and downtime frequency of the equipment, and obtains the delayed procedure index. The material consumption comparison module is based on the delayed process index. It analyzes the material usage and worker workload of each process, and combines the data of rebar binding and concrete pouring to calculate the daily material consumption in real time. It compares the calculated material consumption with the predetermined material supply to determine the amount of additional material needed. It also screens the key processes and material types with insufficient material supply to obtain material gap analysis data. The inventory response adjustment module analyzes the current inventory status and material outbound frequency based on material shortage analysis data. It calculates whether the inventory level can meet short-term construction needs based on the time it takes to transport materials to the construction site, and adjusts the warehouse inventory level for predicted material shortages to obtain the inventory adjustment configuration. The logistics optimization decision module is based on inventory adjustment configuration, obtains the types of materials that need to be prioritized for delivery, analyzes the application frequency and criticality of materials in bridge construction, optimizes logistics based on the urgent supply needs of materials and the dependencies between processes, and generates priority delivery indicators. The supply chain assessment module uses priority delivery indicators to examine the deviation between the actual and expected material delivery times in the supply chain, analyzes the material demand and supply time for the hanging basket section and the side span cast-in-place section, quantifies the supply time deviation, assesses the impact of the deviation on the construction progress, and obtains the material supply analysis results.

[0024] The delayed process index includes process number, delay duration, and key influencing factors; the material gap analysis data includes gap material type, gap quantity, and key processes; the inventory adjustment configuration includes adjustment amount and delivery adjustment results; the priority delivery indicators include material type, delivery priority, and dependent processes; and the material supply analysis results include deviation amount, impact assessment results, and demand matching degree.

[0025] like Figure 2 and Figure 3 As shown, the schedule deviation analysis module includes: The process time processing submodule is based on the construction task of the main beam section of the bridge. It collects the planned completion time and actual completion time of each process, calculates the time difference, and identifies the time difference with the process number to establish a process time difference marker. Obtain the main beam segment construction schedule and extract information for all work procedures. Fields include the procedure number (e.g., ZL-001), planned start date (e.g., April 1, 2025), and planned completion date (e.g., April 5, 2025). Then, retrieve the construction log and extract the actual start time (e.g., April 2, 2025) and actual completion time (e.g., April 7, 2025) from the site records. Calculate the date difference between the actual completion time and the planned completion time to obtain the construction offset time for each procedure. For example, the planned duration of process ZL-001 is 5 days, from April 1st to April 5th, and the actual duration is 6 days, from April 2nd to April 7th. The time difference is +1 day, which means a delay of 1 day. Combine "ZL-001" with the time difference "+1 day" to form a time difference record. Process all processes one by one in this way to build a complete list of process time differences. Then, sort and archive the time difference information according to the process number or construction logic order, mark the delay, early completion or on-time completion status of each process, and form a structured data table.

[0026] The equipment operation efficiency submodule analyzes the equipment operation time and actual operation time corresponding to the construction process based on the process time difference mark, calculates the equipment operation efficiency in a single time period, forms a corresponding sequence of efficiencies according to the process sequence, and matches the position with the process time difference mark to obtain an efficiency coefficient matching table. After establishing the process time difference markers, each process number is processed item by item. The equipment operation information associated with the process is filtered, and the total operating time of the equipment during the construction period is extracted. For example, for the concrete vibration process numbered ZL-002, the associated equipment is the HZD-3 vibrator. This equipment operated for a total of 32 hours during the actual construction period of the process. At the same time, the actual operation time information of the process is called up. For example, the actual construction period of ZL-002 is from April 10 to April 13, 2025, and the total construction time is 4 days, or 96 hours. By converting 32 hours to 96 hours, the operating efficiency of the equipment in this process is calculated to be 0.33, or 33%. The efficiency data of all processes are organized according to the process logic order. After generating a sequence, it is matched with the time difference marker table. Combined with the process number, each efficiency value and its corresponding process time difference are merged and recorded to form an efficiency coefficient matching table.

[0027] The key process screening submodule obtains the equipment failure downtime of each process based on the efficiency coefficient matching table, calculates its proportion in the total working hours, and filters the process numbers with large deviation and low efficiency to obtain the delayed process index. The efficiency coefficient matching table is analyzed item by item. After reading the process number, the equipment downtime record database is accessed. All equipment failure time periods during the construction period of that process are retrieved. The start and end times of each failure are extracted, and the duration difference is accumulated to calculate the total downtime. For example, the construction period for process ZL-003 is from April 15th to April 19th, 2025, totaling 5 days and 120 hours. The vibrator equipment failed 3 times, with downtimes of 1 hour, 2 hours, and 3 hours respectively, totaling 6 hours, accounting for 5% of the total construction time. This value is then combined with the equipment efficiency and time difference of the current process for a composite judgment, and a setting is made. The criteria for judgment are: equipment efficiency is less than 0.30 (i.e., less than 30%), time difference is greater than or equal to 2 days, and downtime due to failure accounts for more than 5%. For example, ZL-003 has an efficiency of 0.28, a time difference of +3 days, and an equipment downtime ratio of 5%. If the above three conditions are met, the process is marked as a delayed process. This type of judgment action is performed on all records in sequence, and the process numbers that meet the conditions are filtered to output a list of delayed process indexes, including the fields "process number", "efficiency value", "time difference (days)" and "failure percentage (%)". For example, a record is "ZL-003, 0.28, +3, 5%".

[0028] like Figure 2 and Figure 4 As shown, the material consumption comparison module includes: The process usage assessment submodule is based on the delayed process index. It collects the material usage records and worker working hours of the corresponding process. By statistically analyzing the man-hour material usage in a single process, it compares it with the historical average usage of the process to identify material usage deviations and obtain the material offset range. The material usage records for each delayed process are retrieved from the construction material management database. Information such as material type, actual usage of each material, reporting unit, and usage period are extracted. Simultaneously, the working hours data for all workers involved in the process are obtained from the construction team's shift schedule. The total daily working hours for each worker are calculated and summarized by name and shift. For example, for the concrete pouring process numbered GZ-021, the material usage record shows an actual concrete usage of 24 cubic meters, a steel reinforcement usage of 1.8 tons, a construction period from February 2nd to February 5th, 2025, and 6 workers in the team working 8 hours per day, for a total working time of 192 hours. The above material usage data and total worker working hours are integrated to construct a man-hour usage dataset. Then, the average working hours for similar processes are retrieved from historical construction data. The average material usage and average man-hours are used. For example, in 10 historical projects, the average concrete usage for the same process is 20 cubic meters, the average steel reinforcement is 1.6 tons, and the average man-hours are 180 hours. The difference is calculated by subtracting the current actual data from the historical average. Then, the difference is compared with the average to determine the percentage deviation of the current process material usage. If the deviation exceeds a set threshold (set to ±10%), it is identified as an offset. The 10% threshold is set based on the average standard deviation of historical data. For example, if the concrete deviation is 20%, the steel reinforcement deviation is 12.5%, and the man-hour deviation is 6.7%, the first two exceed the offset identification threshold. The offset range is recorded as a positive deviation, that is, the usage is greater than the historical benchmark. The above offset is then mapped one-to-one with the process number to generate material offset range data.

[0029] The daily consumption calculation submodule analyzes the data of rebar tying and concrete pouring based on the material offset range, calculates the daily material usage for each process, compares the actual usage with the planned supply, determines the difference between the daily consumption and supply of each material, and obtains the daily consumption difference record. Analyze the data on rebar tying and concrete pouring, calculate the daily material usage for each process, compare the actual usage with the planned supply, and use the following formula: ; Determine the first Daily consumption difference of various materials ,in, Representing the The volume requirement in a process refers to the volume of materials needed for a specific process, such as rebar tying or concrete pouring, and is one of the important factors affecting material consumption. Representing the The unit material consumption rate of a process indicates how much material is required per unit volume, and is derived from historical data or engineering standards. Representing the The planned supply quantity of a material is a pre-set supply quantity based on the project plan and material supply strategy, used for comparison with the actual usage. Represents the total number of processes; In analyzing data on rebar tying and concrete pouring, the material usage for each process is calculated using volumetric requirements and unit material consumption rates. The sum of these calculations is then compared with the planned supply to determine the daily material consumption difference. The following specific parameter values ​​were obtained from actual engineering data monitoring: Total number of processes (Rebar tying and concrete pouring) For the first process (rebar tying): Volume requirements cubic meters; Unit material consumption rate tons per cubic meter; For the second process (concrete pouring): Volume requirements cubic meter; Unit material consumption rate tons per cubic meter; Planned supply ton; Calculate the material usage for each process: Material usage for the first process: ton; Material usage for the second process: ton; Calculate the total material usage: Total material usage ; Calculate the daily consumption difference: ; The results indicate that the actual amount of material used was 20 tons less than the planned supply, suggesting room for optimization in material management and supply chain adjustments. More accurate demand forecasting and supply adjustments could reduce resource waste and costs.

[0030] The material shortage screening submodule calls the daily consumption difference record to evaluate the degree of material shortage in each process, sorts them from high to low according to the amount of material shortage, identifies the key processes and material types with insufficient material supply, and obtains material gap analysis data. The difference data for each material in each process is statistically summarized. First, the daily differences of the same material in the same process are accumulated to obtain the total shortage quantity of the material in that process. At the same time, it is determined whether the daily difference of the material is positive on any given day, that is, the actual usage on that day is greater than the planned supply. If this occurs more than or equal to 2 times, it is marked as a frequent shortage item. For example, in the concrete pouring process GZ-023, the actual usage exceeded the supply plan on 3 out of 5 days, with a total difference of 1.4 cubic meters and a maximum single-day difference of 0.6 cubic meters. This material is marked as a shortage item. The screening threshold is set as the shortage quantity exceeding the material The material shortage is calculated as 10% of the total planned material quantity. This value is based on the average proportion of material shortage data from historical projects. If the total planned material supply is 10 cubic meters, 10% is 1 cubic meter. When the total shortage exceeds 1 cubic meter, it is marked as a serious shortage. Then, all the short-supply materials are sorted from high to low according to the shortage amount, and the fields such as the process number, material name, total shortage amount, shortage frequency, and maximum single-day shortage are recorded to form a list of key material shortages. For example, concrete (process GZ-023, shortage 1.4 m³) and steel bars (process GZ-024, shortage 0.9 tons) are output as material shortage analysis data.

[0031] like Figure 2 and Figure 5 As shown, the inventory response adjustment module includes: The inventory status detection submodule collects the current inventory of materials and recent outbound records based on the material shortage analysis data, counts the outbound frequency of materials with differences and classifies them by type, compares the ratio of inventory and outbound data, evaluates the circulation speed and consumption rate of each material, and generates an inventory turnover speed index. After extracting the material information from the gap records by number, the warehouse management database is accessed to retrieve the current real-time inventory of the corresponding material. The unit of measurement is tons, cubic meters, or units. An original inventory list is generated after categorizing by material type. For example, the number MT-C20 represents C20 concrete, and its current inventory is 58 cubic meters. Then, all outbound records for this material within the last 15 days are extracted from the outbound records, and the number of outbound trips and total outbound volume are calculated. The time window length is set to 15 days, a value derived from the project's typical construction cycle. Subsequently, the outbound frequency and volume are summarized by material type. For example, MT-C20 was outbound 8 times in 15 days, with a total outbound volume of 40 cubic meters. The daily outbound frequency was calculated to be 0.53 times / day, and the outbound volume frequency was 2.67 cubic meters / day. This was then compared with the current inventory level, resulting in an inventory-to-outbound ratio of 58:40, which is 1.45. The same calculation was then performed on all materials, and their circulation speed and consumption rate were evaluated. Circulation speed was defined as the outbound frequency divided by the time window length, and consumption rate was defined as the average outbound volume per unit time. Evaluation intervals were set as follows: consumption rate less than 1 unit / day was "low-speed zone," 1 to 3 units / day was "medium-speed zone," and greater than 3 units / day was "fast zone." Based on this, MT-C20 was marked as a medium-speed circulating material, forming an inventory turnover speed index table.

[0032] The transportation time calculation submodule calls the inventory turnover speed index to analyze the transportation path and time of each material from the warehouse to the construction site. Combined with the batch transfer frequency and time cost, it calculates the transportation time. Combined with inventory data, it evaluates the construction cycle supported by the materials and obtains the transportation support efficiency. The transportation route and time for each material from the warehouse to the construction site are analyzed using the following formula: ; Calculate the total transportation time It is the total time for all materials to travel from the warehouse to the construction site, of which, Representing the The transportation distance for this type of material is the actual distance along the logistics route. Representing the The transportation speed of this material is determined based on the transportation vehicle and route conditions. Representing the The loading and unloading time for this type of material refers to the time required to load the material from the warehouse onto the transport vehicle and then unload it from the transport vehicle. The number of representative material types; There are three types of materials whose transportation from the warehouse to the construction site needs to be analyzed, and the parameters are derived from actual data monitoring and collection: Material A: Transport distance Kilometers, data obtained through GPS path tracking; Transportation speed km / h, the speed is derived from the average transport speed data of the fleet; Loading and unloading time The hourly rate was determined by tracking the work records of the loading and unloading teams. Material B: Transport distance kilometer; Transportation speed km / h; Loading and unloading time Hour; Material C: Transport distance kilometer; Transportation speed km / h; Loading and unloading time Hour; Substitute the numerical values ​​into the formula to calculate: ; The results show that the total time required to transport all materials is 6.883 hours, reflecting the actual time required from the warehouse to the construction site under given speed and loading / unloading conditions. This is crucial for time management and logistics scheduling of planned projects, helping to accurately assess the material support time on which the overall project schedule depends. The calculation of the total time allows the construction cycle to be optimized and adjusted based on the actual transportation time.

[0033] The outbound dynamic control submodule analyzes material shortage data and current inventory coverage based on transportation efficiency, adjusts material inventory levels to meet current demand, and matches changes in construction needs to obtain inventory adjustment configurations. For each material in the table, an item-by-item judgment operation is performed, retrieving its inventory support period and transportation frequency. This is then compared with the average daily demand for the same material in delayed processes from the material gap analysis data. If a material's inventory support period is lower than its demand coverage period (i.e., the daily demand multiplied by the transportation period is greater than the current inventory), the material is marked as needing adjustment. For example, material MT-C20 has an average daily consumption of 3 cubic meters in process GZ-026, a transportation period of 6 days, and a total demand of 18 cubic meters. The current inventory is only 12 cubic meters, insufficient to support one allocation cycle, thus the inventory needs to be adjusted upwards. Subsequently, this is combined with historical daily averages. The adjustment range is determined by the outbound volume and the current upper limit of the warehouse capacity (e.g., the maximum storage capacity of the warehouse is 100 cubic meters). If the upper limit is not exceeded, the inventory is adjusted according to a safety factor of 1.2, that is, the recommended inventory is adjusted to 22 cubic meters. An adjustment instruction is generated. Then, it is determined whether there is a peak construction period in the next 7 days of the construction plan. If so, for example, the next week is the concentrated construction period of main beam concrete, and the maximum daily consumption is expected to be 6 cubic meters. Then, the adjustment target needs to be further increased to 36 cubic meters. The material number, original inventory, recommended adjustment quantity, recommended adjustment time point, and corresponding construction task number are summarized to form an inventory adjustment configuration table.

[0034] like Figure 2 and Figure 6 As shown, the logistics optimization decision module includes: The delivery priority identification submodule identifies material types with high-frequency delivery needs based on inventory adjustment configuration, evaluates the frequency of material outbound and usage, matches the construction schedule, determines the types of materials that need to be prioritized for delivery, and obtains a set of high-frequency materials. Extract the material numbers from all configuration records, retrieve the outbound records for each material within the last 30 days, count the number of outbound trips and the total outbound volume, calculate the average outbound frequency and outbound density per unit time, then call the construction schedule plan to obtain the usage distribution of each material at each construction node within the planned time period and the duration of the corresponding process, and expand the outbound frequency and usage frequency on a daily basis to form a frequency ratio. If the ratio is higher than 1, it indicates that the actual outbound density is higher than the planned usage frequency, which serves as the first criterion for identifying high-frequency delivery materials. For example, material YJ-12 steel bars in the past Within 30 days, there were 15 outbound shipments, totaling 18 tons. The planned usage during the same period was 14 tons, and the planned outbound frequency was 10 times, resulting in a frequency ratio of 1.5. This exceeds the judgment benchmark of 1.2, so it is recorded as a high-frequency material. Subsequently, all recorded materials are traversed and the above calculation process is executed. Materials with an outbound frequency higher than 12 times / month and a frequency ratio higher than 1.2 are selected as target objects. This selection threshold is set based on the median construction frequency of the project, forming an identification table composed of fields such as material number, outbound frequency, planned frequency, outbound density, planned density, and frequency ratio, thus forming a set of high-frequency materials.

[0035] The material application positioning submodule is based on a high-frequency material set. It collects application data of materials in different bridge construction sections, counts the frequency of material use in the hanging basket section and the side span cast-in-place section, and evaluates its criticality and application scope in the construction process to obtain the material application coverage rate. The structural construction logs and material usage records were accessed item by item to identify the application process numbers and construction locations of each high-frequency material in different bridge sections. Sections were then categorized according to bridge structure type, such as marking G1 as the formwork section and E5 as the side span cast-in-place section. The frequency of use of each material in each section was statistically analyzed. For example, material YJ-12 was used in 7 processes and 12 times in the formwork section, while it was used in 2 processes and 3 times in the side span section, a difference of 9 times. The frequency in the formwork section was significantly higher than in the side span section, indicating that its application was mainly concentrated in the formwork section. Subsequently, the application processes corresponding to each material were evaluated in the construction tasks. The criticality of a material is determined by whether it appears on the critical path or whether it has a concurrent or preceding relationship with dependent processes such as concrete pouring. If either condition is met, it is considered a critical material. For example, if 5 out of the 7 processes involved in YJ-12 are critical path tasks, the criticality score is set at 71%, which exceeds the benchmark value of 60%, so it is considered a critical material. Then, the bridge section coverage rate is defined as the number of covered bridge sections divided by the total number of bridge sections according to the material number. If YJ-12 covers 7 sections of the hanging basket section, accounting for 70% of the total 10 hanging basket sections, then the coverage rate is 70%, and the criticality score and coverage rate are recorded together.

[0036] The supply emergency prioritization submodule calls the material application coverage, analyzes the urgent supply demand of materials and the dependencies between processes, assesses the impact of missing materials on upstream processes, prioritizes materials that are critical to construction, and generates priority delivery indicators. First, the current material status is identified from the material arrival record to determine if delivery for the current cycle has been completed. If not, its current status is recorded as "pending arrival." Next, the construction plan is accessed to retrieve all process numbers associated with the material. It is determined whether the process is part of the planned construction tasks within the current time period. If the current time falls within the planned start and end interval and the material has not arrived, a delay flag is set. Then, it is determined whether there are dependencies between processes, i.e., whether downstream processes have completed their preliminary preparations or are awaiting the material's supply. For example, if material YJ-12 corresponds to process GZ-041, and the process is scheduled from April 10th to April 4th... The process was scheduled for April 12th. YJ-12 had not arrived by April 9th. Meanwhile, the GZ-042 process was required to start two days after GZ-041 was completed. It was determined that the absence of GZ-041 material would affect the start of GZ-042 construction. Based on this, the impact of the material on subsequent construction stages was assessed. The degree of impact was set as the number of affected processes divided by the total number of processes involved by the material. If YJ-12 affected 4 subsequent processes, involving a total of 6 processes, the impact ratio was 66%. Materials with an impact ratio exceeding 50%, a criticality score exceeding 60%, and an application coverage exceeding 60% were prioritized, and a priority delivery index data table was generated.

[0037] like Figure 2 and Figure 7 As shown, the supply chain assessment module includes: The delivery time offset submodule uses priority delivery indicators to obtain the actual and scheduled delivery times of related materials. By comparing the time data, it calculates the delivery time deviation for each type of material, assesses the impact of the deviation on supply chain efficiency, and obtains the delivery deviation area. The system retrieves the actual and scheduled arrival times of materials from warehouse arrival records and supply contracts. A time comparison table is created, mapping each material number to its corresponding date. For each material, a date difference calculation is performed, subtracting the scheduled arrival time from the actual arrival time to obtain the offset in days. For example, steel bar number CL-A01, scheduled for arrival on June 3, 2025, actually arrived on June 5, 2025, resulting in an offset of +2 days, indicating a 2-day delay. This same calculation is performed on all materials. The offset values ​​are then categorized by material type, and the offset frequency and average offset time are calculated. Furthermore, offset values ​​are classified as negative offsets (increased offsets). There are three types of delivery deviations: early arrival, zero deviation (on-time arrival), and positive deviation (delayed arrival). For delayed arrival materials, they are divided into three categories based on the number of days of deviation: mild (1 day), moderate (5 days), and severe (more than 5 days). If CL-A01 belongs to the moderate deviation category, it is marked as a secondary deviation item. Then, the percentage of each type of deviation item in all high-frequency materials is statistically analyzed. For example, there are a total of 7 moderate deviation materials, accounting for 35% of the total number of high-frequency materials. If this percentage is higher than the set threshold of 30%, it is marked as a dense deviation area. This threshold is set based on the statistical results of the average percentage of delivery deviations in past projects, forming a delivery deviation area dataset.

[0038] The demand process matching submodule analyzes the matching of material usage time and supply time for the hanging basket section and the side span cast-in-place section based on the delivery deviation area, evaluates the time coordination between material supply and actual demand, determines whether material supply is synchronized with process demand, and obtains process synchronization efficiency. Identify the usage records of each material in the construction process of the bridge's hanging basket section and side span cast-in-place section according to its material number. Extract the start and end times of the corresponding process from the construction plan database. Determine if this time interval overlaps with the actual material delivery time interval. For example, if material CL-A01 is used for process GL-018, with a planned construction period from June 4th to June 6th, 2025, and the material delivery time is June 5th, a matching delay of 1 day is calculated, and this process is marked as "supply lag". If the actual material delivery time is earlier than or equal to the process start time, it is marked as "synchronous". If it is later than the completion time, it is marked as "synchronous". The time frame is marked as "severe mismatch". After performing the above judgment logic on each process item by item, the number of various matching situations is counted and the matching rate is calculated. The matching rate is defined as the percentage of the number of synchronous processes to the total number of processes. For example, if CL-A01 is used in 5 processes, with 2 synchronous, 2 lagging, and 1 severe mismatch, the matching rate is 40%. Materials with a matching rate of less than 60% are marked as "matching offset", matching rates of 60% to 80% are "tolerable offset", and matching rates of more than 80% are "highly synchronous". This partition sets a collaborative efficiency evaluation standard based on the tolerance range of construction rhythm and the safety buffer time requirements, and generates a process synchronization efficiency table.

[0039] The schedule impact assessment submodule analyzes the process delays caused by material supply delays based on the process synchronization efficiency, assesses the potential impact of the delays on the construction project schedule, quantifies the degree of impact, optimizes future material supply and process arrangement, and obtains material supply analysis results. Perform a delay analysis on each record, identify all process numbers marked as "supply lag" or "severe mismatch," obtain their planned start time and actual start time, calculate the actual delay days for each process, and then determine whether the process is a critical path task or a multi-process concurrent node. For example, process GL-018 was planned to start on June 4th, but actually started on June 6th, a delay of 2 days. If this process is on the critical path and the delay propagates to downstream processes causing continuous delays, then its delay impact is assigned a value of 100%. For non-critical path processes, the delay is determined based on downstream processes. The impact value is assigned based on the degree of transmission. For example, if the delay does not affect any subsequent process, the impact value is set to 0%. If it affects one subsequent process and the delay of that process is 1 day, it is recorded as a moderate impact and the impact level is set to 50%. Based on this, the impact calculation is performed on the processes corresponding to all delayed materials. The total number of delay days and the average impact value of the processes involved in each type of material are calculated. For example, the process corresponding to CL-A01 is delayed for a total of 7 days and the average impact is 62%. Materials with a delay level of more than 3 days and an average impact value of more than 50% are marked as "severe impact". A material supply analysis result table is constructed.

[0040] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0041] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0042] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0043] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0044] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0045] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0046] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0047] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0048] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0049] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A bridge construction material management system based on big data, characterized in that, The system includes: The schedule deviation analysis module is based on the construction task of the main girder section of the bridge. It obtains the work procedures, equipment operation time and equipment failure downtime, records the difference between the actual completion time and the planned completion time of each procedure, and identifies the key factors that cause construction delays by comparing the operating efficiency and downtime frequency of the equipment, and obtains the delayed procedure index. The material consumption comparison module analyzes the material usage and worker workload of each process based on the delayed process index. Combined with the data on rebar tying and concrete pouring, it calculates the daily material consumption in real time, determines the amount of additional materials needed, and obtains material shortage analysis data. The inventory response adjustment module analyzes the current inventory status and material outbound frequency based on the material shortage analysis data, calculates whether the inventory level can meet short-term construction needs based on the time it takes to transport materials to the construction site, adjusts the warehouse inventory level, and obtains the inventory adjustment configuration. Based on the aforementioned inventory adjustment configuration, the logistics optimization decision module analyzes the application frequency and criticality of materials in bridge construction, optimizes logistics according to the urgent supply needs of materials and the dependencies between processes, and generates priority delivery indicators.

2. The bridge construction material management system based on big data according to claim 1, characterized in that, The delayed process index includes process number, delay duration, and key influencing factors; the material gap analysis data includes gap material type, gap quantity, and key processes; the inventory adjustment configuration includes adjustment amount and delivery adjustment result; and the priority delivery index includes material type, delivery priority, and dependent processes.

3. The bridge construction material management system based on big data according to claim 1, characterized in that, The schedule deviation analysis module includes: The process time processing submodule is based on the construction task of the main beam section of the bridge. It collects the planned completion time and actual completion time of each process, calculates the time difference, and identifies the time difference with the process number to establish a process time difference marker. Based on the process time difference marker, the equipment operation efficiency submodule analyzes the equipment operation time and actual operation time corresponding to the construction process, calculates the equipment single-period operation efficiency, forms a corresponding sequence of efficiencies according to the process sequence, and performs position matching with the process time difference marker to obtain an efficiency coefficient matching table. The key process screening submodule obtains the equipment failure downtime of each process according to the efficiency coefficient matching table, calculates its proportion in the total working hours, and filters out process numbers with large deviations and low efficiency to obtain the delayed process index.

4. The bridge construction material management system based on big data according to claim 1, characterized in that, The material consumption comparison module includes: The process usage assessment submodule, based on the delayed process index, collects material usage records and worker working hours for the corresponding process. By statistically analyzing the man-hour and material usage within a single process, it compares the data with the historical average usage of the process to identify material usage deviations and obtain the material offset range. The daily consumption calculation submodule analyzes the data of steel bar binding and concrete pouring based on the material offset range, calculates the daily material usage for each process, compares the actual usage with the planned supply, determines the difference between the daily consumption and supply of each material, and obtains a record of the daily consumption difference. The material shortage screening submodule calls the daily consumption difference record to evaluate the degree of material shortage in each process, sorts them from high to low according to the shortage amount, identifies the key processes and material types with insufficient material supply, and obtains material gap analysis data.

5. The bridge construction material management system based on big data according to claim 4, characterized in that, The analysis of rebar tying and concrete pouring data calculates the daily material usage for each process, compares the actual usage with the planned supply, and uses the following formula: ； Determine the first Daily consumption difference of various materials ,in, Representing the Volume requirements in each process Representing the The unit material consumption rate of each process, Representing the The planned supply of this material This represents the total number of processes.

6. The bridge construction material management system based on big data according to claim 1, characterized in that, The inventory response adjustment module includes: The inventory status detection submodule collects the current inventory of materials and recent outbound records based on the material shortage analysis data, counts the outbound frequency of different materials and classifies them by type, compares the ratio of inventory and outbound data, evaluates the circulation speed and consumption rate of each material, and generates an inventory turnover speed index. The transportation time calculation submodule calls the inventory turnover speed index to analyze the transportation path and time of each material from the warehouse to the construction site. Combined with the batch transfer frequency and time cost, it calculates the transportation time. Combined with the inventory data, it evaluates the construction cycle supported by the materials and obtains the transportation support efficiency. The outbound dynamic control submodule analyzes the material shortage data and the current inventory coverage based on the transportation support efficiency, adjusts the material inventory level according to the current demand, matches the changes in construction demand, and obtains the inventory adjustment configuration.

7. The bridge construction material management system based on big data according to claim 6, characterized in that, The analysis of the transportation route and time for each material from the warehouse to the construction site uses the following formula: ； Calculate the total transportation time ,in, Representing the The transportation distance of the materials Representing the The transportation speed of this material Representing the Loading and unloading time of various materials The number of representative material types.

8. The bridge construction material management system based on big data according to claim 1, characterized in that, The logistics optimization decision-making module includes: The delivery priority identification submodule identifies material types with high-frequency delivery needs based on the inventory adjustment configuration, evaluates the frequency of material outbound and usage, matches the construction schedule, determines the types of materials that need to be prioritized for delivery, and obtains a set of high-frequency materials. The material application positioning submodule collects application data of materials in different bridge construction sections based on the high-frequency material set, counts the frequency of material use in the hanging basket section and the side span cast-in-place section, and evaluates its criticality and application scope in the construction process to obtain the material application coverage rate. The supply emergency prioritization submodule calls the material application coverage, analyzes the urgent supply demand of materials and the dependencies between processes, assesses the impact of undelivered materials on upstream processes, prioritizes materials that are critical to construction, and generates priority delivery indicators.

9. The bridge construction material management system based on big data according to claim 1, characterized in that, The system also includes: The supply chain assessment module uses the priority delivery index to check the deviation between the actual material delivery time and the expected delivery time in the supply chain, analyze the material demand and supply time of the hanging basket section and the side span cast-in-place section, quantify the supply time deviation, assess the impact of the deviation on the construction progress, and obtain the material supply analysis results. The material supply analysis results include deviation, impact assessment results, and demand matching degree.

10. The bridge construction material management system based on big data according to claim 9, characterized in that, The supply chain assessment module includes: The delivery time offset submodule uses the priority delivery index to obtain the actual arrival time and scheduled arrival time of related materials. By comparing the time data, it calculates the arrival time deviation of each type of material, evaluates the impact of the deviation on supply chain efficiency, and obtains the delivery deviation area. Based on the delivery deviation area, the demand process matching submodule analyzes the matching between the material usage time and supply time of the hanging basket section and the side span cast-in-place section, evaluates the time coordination between material supply and actual demand, determines whether the material supply is synchronized with the process demand, and obtains the process synchronization efficiency. The schedule impact assessment submodule analyzes the process delays caused by material supply delays based on the process synchronization efficiency, assesses the potential impact of the delays on the construction project schedule, quantifies the degree of impact, optimizes future material supply and process arrangement, and obtains material supply analysis results.

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