Comprehensive management system of concrete mixing plant

Abstract

The invention discloses an integrated management system for a concrete mixing plant, and relates to the technical field of mixing plant management, a data acquisition unit is accessed to a raw material supplier system to acquire raw material supply data and concrete usage plans in different time periods, and a demand prediction unit introduces meteorological information and construction site states to predict the concrete usage plans in different time periods. And the dynamic optimization module substitutes the raw material supply data and the concrete dosage demand result into a dynamic adjustment model, the dynamic adjustment model dynamically adjusts the stirring progress, a stirring task queue is established, and the production sequence is intelligently sorted according to the material supply condition and the delivery priority. The management system not only can automatically generate a stirring task queue according to the material arrival condition and the construction usage priority, effectively avoid raw material waste and production plan conflicts, but also can adjust the delivery time, the loading sequence and the vehicle scheduling path in a linkage manner, break through the management breakpoint between production and transportation, and improve the production efficiency. And the overall cooperation efficiency and the customer response speed are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of mixing station management, and in particular to a comprehensive management system for a concrete mixing station. Background Art

[0002] With the development of information technology, especially the continuous maturity of technologies such as automation control, Internet of Things, big data and cloud computing, a technical foundation has been provided for the information upgrade of concrete mixing plants. The comprehensive management system of concrete mixing plants has come into being. It aims to digitize, automate and intelligently integrate various links of the mixing station, including raw material procurement, inventory management, production scheduling, equipment monitoring, quality control, transportation management and data reporting, to achieve unified management and refined operation of the entire process of the mixing station.

[0003] The existing technology has the following defects:

[0004] The traditional management model of mixing plants generally relies on manual experience for planning and scheduling. There is usually a delay or asynchrony in the information between raw material supply and construction site demand, making it impossible to achieve accurate prediction and real-time adjustment. Once there is a temporary shortage of raw materials or a sudden increase in orders at the construction site, the mixing plant is often unable to respond in time, which can easily lead to production interruptions, vehicle waiting, customer complaints, and even project delays. At the same time, due to the lack of a systematic data coordination mechanism, raw material inventory is often in an alternating state of "tight-surplus", which not only affects operational efficiency, but also increases management costs and environmental burdens.

[0005] Based on this, the present invention proposes a comprehensive management system for concrete mixing stations, which can not only automatically generate a mixing task queue based on the arrival of materials and the priority of construction usage, effectively avoiding waste of raw materials and production plan conflicts, but also jointly adjust the delivery time, loading sequence and vehicle scheduling path, breaking through the management breakpoints between production and transportation, and improving overall collaborative efficiency and customer response speed. Summary of the Invention

[0006] The purpose of the present invention is to provide a comprehensive management system for a concrete mixing plant to solve the deficiencies in the background technology.

[0007] In order to achieve the above-mentioned object, the present invention provides the following technical solutions: a comprehensive management system for a concrete mixing plant, comprising a data acquisition unit, a demand forecasting unit, and a dynamic optimization module;

[0008] Data acquisition unit: access to the raw material supplier system to obtain raw material supply data and concrete usage plans for different time periods;

[0009] Demand forecasting unit: Introducing meteorological information and construction site conditions, based on the basic concrete usage plan, combined with the meteorological impact coefficient and the construction site condition adjustment coefficient, predicts the concrete demand. The expression is: , where is the predicted concrete demand,[[]]END]] is the planned amount of basic concrete,[[]]END]] is the meteorological influence coefficient,[[]]END]] is the adjustment coefficient of the construction site status,[[]]END]] , are the weight coefficients, and ;

[0010] Dynamic optimization module: Substitute the raw material supply data and the concrete usage demand result into the dynamic adjustment model. The dynamic adjustment model dynamically adjusts the mixing progress, and the expression is: , where is the adjusted production speed,[[]]END]] is the predicted concrete usage demand,[[]]END]] is the maximum capacity that can be borne, and a mixing task queue is established to intelligently sort the production order according to the material supply status and the shipping priority.[[]]END]]

[0011] In a preferred embodiment, the dynamic optimization module receives the raw material supply data from the data acquisition unit and the concrete usage demand data output by the demand prediction unit, synchronously aligns the raw material data and the demand data according to the time dimension. The raw material supply data includes the current inventory level, the in-transit transportation status, and the estimated replenishment cycle. The demand data includes the predicted values of the concrete consumption of each construction site during the corresponding time period.[[]]END]]

[0012] In a preferred embodiment, the dynamic optimization module takes the raw material supply data and the concrete usage demand result as input variables and substitutes them into the dynamic adjustment model. The dynamic adjustment model dynamically calculates the maximum capacity and production rhythm that the mixing plant can bear in each time period based on the current inventory sufficiency, transportation risk assessment, and future supply guarantee level;[[]]END]]

[0013] After the dynamic adjustment model outputs the production load curve, a mixing task queue is established according to the shipping requirements and priority requirements of different construction projects. Each mixing task corresponds to a concrete batch order;[[]]END]]

[0014] Based on the material supply status and the shipping priority, the weighted sorting algorithm is used to intelligently arrange the production order. After determining the priority order of the mixing tasks, the shipping time of each batch of concrete is dynamically adjusted according to the predicted result of the completion time of the mixing tasks, and the loading order is planned.[[]]END]]

[0015] In a preferred embodiment, the processing logic of the dynamic adjustment model is:[[]]END]]

[0016] Obtain the sufficiency index, transportation risk coefficient, and future supply guarantee index, and calculate the maximum capacity that the mixing plant can bear at the current stage.[[]]END]]

[0017] In a preferred embodiment, calculate the maximum production capacity that the mixing plant can carry at the current stage, and the expression is: , where, is the maximum production capacity that can be carried, is the nominal maximum production capacity of the mixing plant, means to select the minimum value, is the adequacy index, SAI is the future supply guarantee index, and TRC is the transportation risk coefficient.

[0018] In a preferred embodiment, the calculation logic of the adequacy index is: obtain the adequacy index by dividing the current raw material inventory by the amount of raw materials required for concrete production within the corresponding time period;

[0019] The calculation logic of the transportation risk coefficient is: obtain the transportation risk coefficient by dividing the recorded transportation delay time by the normal transportation time;

[0020] The calculation logic of the future supply guarantee index is: obtain the future supply guarantee index by dividing the recently promised delivery volume of the supplier by the amount of raw materials required in the future time period in the production plan.

[0021] In a preferred embodiment, the demand forecasting unit introduces meteorological information, including rainfall, temperature, humidity, and wind speed, to generate a meteorological impact coefficient;

[0022] Access the construction site status data, including the actual construction progress, the operation arrangement of the construction team, and the status of the on-site construction surface, to generate a construction site status adjustment coefficient.

[0023] In a preferred embodiment, the calculation of the construction site status adjustment coefficient includes the following steps:

[0024] Obtain the construction progress deviation by subtracting the construction plan progress from the actual completed progress, and obtain the working surface deviation by subtracting the expected working surface ratio from the ratio of the actual available working surface on-site;

[0025] Normalize the construction progress deviation and the working surface deviation so that the value ranges of the construction progress deviation and the working surface deviation are mapped to between [0, 1] to obtain the normalized value of the construction progress deviation and the normalized value of the working surface deviation;

[0026] Sum the normalized value of the construction progress deviation and the normalized value of the working surface deviation to obtain the construction site status adjustment coefficient.

[0027] In a preferred embodiment, the calculation of the meteorological impact coefficient includes the following steps:

[0028] The rainfall impact weight is set according to the rainfall probability and expected rainfall amount in the weather forecast, and the rainfall factor is calculated;

[0029] Get the predicted maximum temperature on the day, set the high temperature impact weight, and obtain the high temperature factor. If the meteorological department issues a severe convective weather alert or a red alert for heavy rain, obtain the comprehensive meteorological alert factor.

[0030] The meteorological impact coefficient is obtained by adding the rainfall factor, the high temperature factor and the comprehensive meteorological warning factor.

[0031] In a preferred embodiment, the data acquisition unit connects with the raw material supplier system to collect raw material supply data in real time, including obtaining the current inventory quantity of each type of raw material, the transportation status of the raw material in transit, the expected arrival time, and the supply cycle information;

[0032] Linked to the construction site project management system, obtain concrete consumption plans for different construction stages, including the specific concrete demand in each future time period, demand period and corresponding project number.

[0033] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0034] The present invention accesses the raw material supplier system through a data acquisition unit to obtain raw material supply data and concrete usage plans for different time periods. The demand forecasting unit incorporates meteorological information and construction site status to predict concrete usage demand. The dynamic optimization module substitutes the raw material supply data and concrete usage demand results into a dynamic adjustment model. The dynamic adjustment model dynamically adjusts the mixing progress and establishes a mixing task queue, intelligently sorting the production sequence based on the material supply status and shipping priority. This management system can not only automatically generate a mixing task queue based on the material arrival status and construction usage priority, achieving "flexible production" and effectively avoiding raw material waste and production plan conflicts, but also can jointly adjust the delivery time, loading sequence and vehicle scheduling path, breaking through the management breakpoints between production and transportation, and improving overall collaborative efficiency and customer response speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0036] Figure 1 This is the architecture diagram of the management system of the present invention.

[0037] Figure 2 It is the operation flow chart of the management system of the present invention. Detailed implementation mode

[0038] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0039] Embodiment 1: Please refer to Figure 1 - Figure 2 As shown, a comprehensive management system for a concrete mixing plant in this embodiment includes a data acquisition unit, a demand prediction unit, and a dynamic optimization module;

[0040] Data acquisition unit: Connect to the raw material supplier system to obtain raw material supply data, including current inventory, transportation status, supply cycle and other data, and link to the construction project management system to obtain the concrete usage plan for different time periods. The concrete usage is sent to the demand prediction unit, and the raw material supply data is sent to the dynamic optimization module;

[0041] Demand prediction unit: Introduce meteorological information and construction site status to predict the concrete usage demand, and send the concrete usage demand to the dynamic optimization module;

[0042] Dynamic optimization module: Substitute the raw material supply data and the concrete usage demand results into the dynamic adjustment model. The dynamic adjustment model dynamically adjusts the mixing progress, establishes a mixing task queue, and intelligently sorts the production order according to the material supply status and the shipping priority, so as to realize the "flexible production" of the mixing task, ensure that resources are not wasted and orders are not delayed, and dynamically adjust the shipping time, loading order and vehicle scheduling path according to the mixing progress.

[0043] In this application, the data acquisition unit connects to the raw material supplier system to obtain raw material supply data and the concrete usage plan for different time periods. The demand prediction unit introduces meteorological information and construction site status to predict the concrete usage demand. The dynamic optimization module substitutes the raw material supply data and the concrete usage demand results into the dynamic adjustment model. The dynamic adjustment model dynamically adjusts the mixing progress, establishes a mixing task queue, and intelligently sorts the production order according to the material supply status and the shipping priority. This management system can not only automatically generate a mixing task queue according to the arrival situation of materials and the priority of construction usage, realize "flexible production", effectively avoid waste of raw materials and production plan conflicts, but also link to adjust the shipping time, loading order and vehicle scheduling path, break the management breakpoint between production and transportation, and improve the overall coordination efficiency and customer response speed.

[0044] Please refer to Figure 2As shown in the figure, the specific working process of the management system is as follows:

[0045] The management system accesses the raw material supplier system to obtain raw material supply data, including data such as current inventory, transportation status, and supply cycle. It links with the construction site project management system. After obtaining the concrete usage plan for different time periods, it introduces meteorological information and the status of the construction site, predicts the concrete usage demand, substitutes the raw material supply data and the result of the concrete usage demand into the dynamic adjustment model. The dynamic adjustment model dynamically adjusts the mixing progress, establishes a mixing task queue, and intelligently sorts the production order according to the material supply status and shipping priority, so as to realize the "flexible production" of the mixing task, ensure that resources are not wasted and orders are not delayed, and dynamically adjust the shipping time, loading order, and vehicle dispatching route according to the mixing progress.

[0046] Embodiment 2: The data acquisition unit accesses the raw material supplier system to obtain raw material supply data, including data such as current inventory, transportation status, and supply cycle. It links with the construction site project management system to obtain the concrete usage plan for different time periods. The concrete usage is sent to the demand prediction unit, and the raw material supply data is sent to the dynamic optimization module.

[0047] First, the data acquisition unit docks with the raw material supplier system to collect the raw material supply data in real time. This process not only includes obtaining the current inventory quantities of various raw materials (such as cement, sand and gravel, admixtures, etc.), but also covers dynamic information such as the in-transit transportation status of raw materials, the estimated arrival time, and the supply cycle. By deeply integrating the supplier's Internet of Things system, warehouse management platform, or transportation monitoring system, the data acquisition unit can ensure that the collected data has high real-time and high accuracy, thus providing reliable support for subsequent production decisions. In addition, while obtaining the raw material data, the system can also capture potential supply exception warning information, such as transportation delays, out-of-stock emergencies, etc., laying a foundation for the dynamic optimization module to intervene in advance to adjust the production plan.

[0048] Subsequently, the data acquisition unit links and accesses the construction site project management system to comprehensively obtain the concrete usage plan for different construction stages. By synchronizing with data such as the construction site construction plan, progress nodes, and bill of quantities in real time, the system can accurately master the specific demand quantity, demand time period, and corresponding project number of concrete in each future time period. The data acquisition unit not only extracts the static usage plan, but also can dynamically track the changes in the construction site progress, such as plan adjustments caused by factors such as weather and construction obstacles, and immediately updates the concrete demand data to ensure the timeliness and accuracy of the demand information.

[0049] After obtaining the raw material supply data and the concrete usage plan data, according to the principle of functional shunt, the data acquisition unit sends different types of data to the corresponding modules respectively. The concrete usage plan is transmitted to the demand forecasting unit, which further refines the forecast by combining meteorological data and on-site construction status; while the raw material supply data is directly transmitted to the dynamic optimization module to provide necessary basic data support for the production scheduling and transportation dispatching of subsequent mixing tasks. Through this process, the data acquisition unit not only realizes the efficient integration of key data sources upstream and downstream, but also ensures that subsequent modules can make intelligent decisions based on the most complete and accurate data environment through a reasonable data distribution mechanism, greatly improving the overall system's operation coordination and response speed.

[0050] The demand forecasting unit introduces meteorological information and on-site construction status to predict the concrete usage demand, and the concrete usage demand is sent to the dynamic optimization module.

[0051] After the data acquisition unit completes the preliminary data collection and sends the concrete usage plan, the demand forecasting unit begins to further dynamically forecast the concrete demand. First, the demand forecasting unit introduces meteorological information, including meteorological elements such as rainfall, temperature, humidity, wind speed, etc. By analyzing the weather changes, it predicts the factors that may affect the construction progress. Weather changes have a significant impact on the concrete usage in actual construction. For example, heavy rain may cause construction to pause, while high temperature conditions may accelerate the construction progress, thus triggering temporary fluctuations in concrete demand.

[0052] At the same time, the demand forecasting unit accesses the on-site construction status data, such as the actual construction progress, the operation arrangement of construction teams, and the status of the constructible surface on-site (such as the completion degree of scaffolding erection, the progress of formwork installation, etc.). These on-site status information can further correct the original static usage plan, making the forecast more in line with the current construction reality and reducing resource waste or production arrangement mistakes caused by sudden on-site changes.

[0053] In order to realize the dynamic forecast of concrete demand, the demand forecasting unit adopts the following calculation formula: , where is the predicted concrete demand volume, is the basic concrete usage plan, is the meteorological influence coefficient, is the on-site construction status adjustment coefficient, , are the weight coefficients, and .

[0054] The formula is based on the basic usage plan, and introduces meteorological factors (adjusted by the meteorological influence coefficient) and construction site status factors (adjusted by the construction status adjustment coefficient) respectively. Through the method of weighted summation, the final prediction model is obtained to predict the concrete usage in a suitable state. Among them, and can be trained and optimized according to historical data, and should adapt to the characteristics of different construction projects and climate regions

[0055] The meteorological influence coefficient can be obtained comprehensively based on the meteorological warning level, precipitation probability, temperature anomaly degree, etc. For example, in the case of heavy rain forecast, W takes a negative value (representing a decrease in demand); in the case of fine weather and suitable temperature for construction, W takes a positive value (representing an increase in demand).

[0056] The construction site status adjustment coefficient S is dynamically generated according to the comparison between the construction plan completion rate and the actual completion rate. For example, if the construction is ahead of schedule, S is positive; if the construction is behind schedule, S is negative. The finally calculated dynamic predicted concrete demand Q will be sent to the dynamic optimization module in real time, so that the mixing plant can adjust the production plan and delivery schedule according to the latest predicted demand, realizing the dynamic balance of supply and demand and the optimal utilization of production resources.

[0057] The calculation steps of the meteorological influence coefficient are as follows:

[0058] First, the demand prediction unit connects to the meteorological data platform to obtain the meteorological forecast data in the construction area for a period of time in the future in real time, mainly including key elements such as precipitation probability, precipitation amount, temperature, humidity, wind speed, and weather warning level. Subsequently, the system evaluates the influence trend of meteorology on the concrete usage demand step by step according to the potential influence degree of each meteorological element on the construction activities.

[0059] Set the rainfall influence weight according to the precipitation probability and expected precipitation amount in the meteorological forecast. Through the formula: , in the formula, is the rainfall factor, is the rainfall influence weight, is the precipitation probability, is the expected precipitation amount. Among them, rainfall causes construction interruption or slowdown, so a negative value is taken to represent the potential decrease in concrete demand.

[0060] Obtain the highest temperature on the predicted day and set the high temperature influence weight. When the temperature exceeds the high temperature threshold, it is considered that high temperature may cause construction acceleration or demand increase. The calculation method is: , in the formula, is the high temperature factor, is the high temperature influence weight, is the highest temperature on the predicted day, is the high temperature threshold.

[0061] If the meteorological department issues special warnings such as severe convective weather warnings and red rainstorm warnings, set a warning weight and directly assign a relatively large negative adjustment value. , where is the comprehensive meteorological warning factor, is the warning weight.

[0062] Then the meteorological influence coefficient is obtained by adding the rainfall factor, the high temperature factor, and the comprehensive meteorological warning factor. The meteorological influence coefficient W comprehensively reflects the potential influence degree of weather factors on the construction rhythm. If W>0, it means the weather is favorable for construction and the concrete demand may increase. If W<0, it means the weather is unfavorable for construction and the concrete demand may decrease.

[0063] Meteorological factors are important external variables that directly affect the change of concrete demand. Concrete construction especially depends on weather conditions. Severe weather such as rainfall, strong wind, and extreme high temperature will cause the construction progress to be postponed or interrupted. Therefore, quantifying meteorological elements into the influence coefficient W and dynamically adjusting the prediction through specific meteorological parameters conforms to the actual logic of the construction site.

[0064] The product of the rainfall probability and the rainfall amount reflects the double superposition effect of the possibility of rainfall occurrence and the rainfall degree. By setting the rainfall weight, it can be adjusted according to the differences in the rainfall sensitivity of different projects. For example, the response degrees of open-air operations to light rain and heavy rain are different, and the weight can reflect this difference.

[0065] When the high temperature exceeds the suitable construction range (such as exceeding 35°C), the concrete pouring may be accelerated to prevent the concrete from cracking due to early water loss. Therefore, it is in line with the actual situation to cause a positive adjustment when the temperature exceeds the threshold. When the threshold is not exceeded, irrelevant weather fluctuations can be avoided from interfering with the prediction.

[0066] Meteorological warnings are often the direct basis for major construction adjustments. Therefore, setting an independent and relatively large negative adjustment item to quickly lower the demand prediction when the system detects the warning signal can ensure the rapid response of the management system to sudden weather conditions.

[0067] Overall superposition model: Add up the influences of rainfall, high temperature, and extreme weather. It can not only reflect the change trend of a certain factor alone, but also comprehensively consider the superposition effect of multiple weather factors. This linear superposition method is simple and effective, avoiding the overfitting problem of complex non-linear models, and is convenient for quick adjustment and manual intervention in actual engineering applications.

[0068] Therefore, the design of the meteorological influence coefficient W can reflect the influence of climate change on the concrete demand for construction in real time and flexibly, ensuring that the prediction results have sufficient sensitivity and accuracy.

[0069] The calculation steps of the construction site status adjustment coefficient are as follows:

[0070] While introducing meteorological information in parallel, the demand forecasting unit also accesses the construction site status information, including indicators such as the actual construction progress, the arrival situation of construction resources, and the constructible ratio of the on-site working face. The system dynamically calculates the construction status adjustment coefficient S according to the deviation degree between the actual situation on site and the planned progress.

[0071] Calculation of construction progress deviation: Obtain the construction progress deviation by subtracting the construction plan progress from the actual completed progress. A positive value represents that the construction is ahead of schedule, and a negative value represents that the construction is behind schedule.

[0072] Calculation of working face deviation: Evaluate the ratio of the actually available working face for construction on site, compare it with the expected working face ratio, and obtain the working face deviation, that is, obtain the working face deviation by subtracting the expected working face ratio from the actually available working face ratio for construction on site; the larger the working face deviation, the more working faces there are, then the demand for concrete pouring increases, and the smaller the working face deviation, the more restricted the working face is, then the demand decreases.

[0073] Then, normalize the construction progress deviation and the working face deviation, map the value ranges of the construction progress deviation and the working face deviation to between [0, 1], obtain the normalized value of the construction progress deviation and the normalized value of the working face deviation, and sum the normalized value of the construction progress deviation and the normalized value of the working face deviation to obtain the construction site status adjustment coefficient.

[0074] When the construction is ahead of schedule and the working face is sufficient, S > 0, indicating that the concrete demand will be higher than the original plan. When the construction is behind schedule and the working face is restricted, S < 0, indicating that the concrete demand will be lower than the original plan.

[0075] The construction site status is the part that has the most direct impact on the change of the actual concrete demand among the internal factors. The actual progress of the construction, whether the working face is sufficient, and whether the construction resources have arrived will all determine the concrete usage amount of the construction unit in the future period. Abstracting these factors into quantitative indicators and obtaining the adjustment coefficient S in a linear addition manner has a very clear practical basis.

[0076] Construction progress deviation: The difference between the actual construction progress and the planned progress is the main source of demand change. If the construction is ahead of schedule, naturally more concrete is needed than planned. If the construction is behind schedule, the concrete demand decreases. It can quickly and intuitively reflect the change trend of the construction progress rhythm.

[0077] Working face availability deviation: Even if the overall construction progress is normal, if the currently available working face for construction is insufficient, it will also suppress the concrete demand. The difference in the working face ratio reflects the direct impact of the space preparation status on the demand change, and is a necessary supplement for further refining the progress analysis.

[0078] The construction status is the result of the combined action of multi-dimensional factors and should not be determined by a single indicator. Therefore, the design of the on-site construction status adjustment coefficient S can comprehensively and multi-angularly reflect the dynamic changes on-site, ensure that the prediction of concrete demand will not be distorted due to on-site detail changes, and at the same time enable the prediction system to have a rapid response ability to changes in the true construction status.

[0079] The dynamic optimization module substitutes the raw material supply data and the concrete usage demand result into the dynamic adjustment model. The dynamic adjustment model dynamically adjusts the mixing progress, establishes a mixing task queue, and intelligently sorts the production order according to the material supply status and the shipping priority, so as to achieve the "flexible production" of the mixing task, ensure that resources are not wasted and orders are not delayed, and dynamically adjust the shipping time, loading order and vehicle scheduling path according to the mixing progress.

[0080] The dynamic optimization module substitutes the raw material supply data and the concrete usage demand result into the dynamic adjustment model. The dynamic adjustment model dynamically adjusts the mixing progress, establishes a mixing task queue, and intelligently sorts the production order according to the material supply status and the shipping priority, so as to achieve the "flexible production" of the mixing task, ensure that resources are not wasted and orders are not delayed, and dynamically adjust the shipping time, loading order and vehicle scheduling path according to the mixing progress, including the following steps:

[0081] First, the dynamic optimization module receives the raw material supply data from the data acquisition unit and the concrete usage demand data output by the demand prediction unit. The system synchronously aligns the raw material data and the demand data according to the time dimension to ensure that the supply and demand data can be matched and analyzed under the same time coordinate. The raw material supply data includes the current inventory level, the in-transit transportation status and the estimated replenishment cycle, and the demand data includes the predicted values of the concrete consumption of each construction site during the corresponding time period.

[0082] Next, the dynamic optimization module takes the raw material supply data and the concrete usage demand result as input variables and substitutes them into the dynamic adjustment model. The dynamic adjustment model aims to ensure continuous production and optimal utilization of resources. Based on the current inventory sufficiency, transportation risk assessment and future supply guarantee level, it dynamically calculates the maximum production capacity and the most reasonable production rhythm that the mixing plant can bear in each time period. The model sets constraint parameters such as the safety inventory threshold of raw materials, the triggering condition for emergency replenishment and the upper limit of production capacity load, and analyzes in real time whether there are potential supply and demand contradictions, and adjusts the mixing speed and production schedule accordingly.

[0083] The dynamic optimization module receives and analyzes the raw material supply data and the concrete usage demand data, and establishes a time series model of the raw material supply status and the concrete demand status. In order to accurately reflect the dynamic relationship between supply and demand, the system needs to establish an inventory sufficiency assessment index for various raw materials, establish a risk assessment model for the transportation process, and form a comprehensive prediction of the future supply situation.

[0084] The processing logic of the dynamic adjustment model is as follows:

[0085] First, obtain the adequacy index by dividing the current raw material inventory by the expected raw material quantity required for concrete production within the corresponding time period. The adequacy index reflects whether the existing inventory can meet the upcoming production demand. An adequacy index value greater than or equal to 1 indicates sufficient inventory, and a value less than 1 indicates a shortage risk, requiring adjustment of the production rhythm or emergency replenishment. Obtain the transportation risk coefficient by dividing the recorded transportation delay duration by the normal transportation time. The transportation risk coefficient is used to measure the current transportation risk level. The larger the transportation risk coefficient value, the higher the uncertainty in the transportation link. It is necessary to reduce the dependence on mixing production and reserve a larger redundancy to avoid production stagnation caused by transportation interruption. Obtain the future supply security index by dividing the recently promised delivery quantity by the raw material quantity required in the future time period in the production plan. The future supply security index evaluates the future stability of the supply chain. When the future supply security index value is less than 1, it indicates a potential supply shortage risk in the future, and it is necessary to adjust the production rhythm in advance or find alternative supplies.

[0086] Calculate the maximum capacity that the mixing plant can bear at the current stage. The expression is: where, is the maximum bearable capacity, is the nominal maximum capacity of the mixing plant, represents selecting the minimum value, is the adequacy index, SAI is the future supply security index, and TRC is the transportation risk coefficient.

[0087] Dynamically adjust the production speed based on the maximum bearable capacity. The expression is: where, is the adjusted production speed, is the predicted concrete consumption demand, is the maximum bearable capacity.

[0088] After the dynamic adjustment model outputs the production load curve, the system establishes a mixing task queue based on the delivery requirements and priority requirements of different construction projects. Each mixing task corresponds to a concrete batch order. The queue sorting comprehensively considers multiple factors, including the importance of the project, the urgency of the construction progress at the construction site, the difference in concrete strength grades, the transportation time window, etc. The dynamic optimization module intelligently arranges the production order based on the material supply situation and delivery priority using a weighted sorting algorithm, giving priority to meeting the orders of projects with high urgency and high importance, and avoiding obstacles to important projects caused by material shortages or production delays.

[0089] To achieve efficient production and accurate delivery of concrete batching plants, the dynamic optimization module establishes a mixing task queue based on the delivery needs and priority requirements of different construction projects. Each mixing task corresponds to a concrete batch order. The construction and sorting of the queue not only considers a single factor, but also comprehensively considers multiple dimensions to ensure that resources are prioritized for the most important and urgent projects. The specific steps include the following:

[0090] The system first obtains information on all pending mixing tasks. Each task is associated with a concrete batch order. This information includes, but is not limited to, project name, project importance score, current construction progress, required concrete strength grade, planned delivery window, and estimated transportation time. This basic data is provided synchronously by the construction site project management system and is updated in real time.

[0091] Based on the construction site schedule and the latest site status, the Construction Urgency Factor (CUF) of each task is calculated. If a task delay may cause a construction break or stoppage, the CUF value will automatically increase to increase the weight of the task in the sorting. .

[0092] Considering the production difficulty and switching cost of different concrete strength grades (such as the need to clean the mixer between batches of different strength grades), the system sets a strength matching factor (SMF) for different strength grades. If the strength grades of adjacent batches are close, they will be prioritized to reduce cleaning and switching losses and improve continuous production efficiency. : .

[0093] The Transport Window Tightness Factor (TWF) is calculated based on the earliest and latest receiving times required by the construction site. The narrower the window, the higher the TWF value, indicating that the production and delivery of the batch must be arranged more accurately. : .

[0094] The dynamic optimization module performs a weighted calculation on the above factors to form the total ranking score for each mixing task. The ranking formula is as follows: , where is the total ranking score, 、 、 is the weight, 、 、 、 They are the evaluation scores of the above-mentioned factors respectively, which have been standardized to a unified range (such as between 0 and 1).

[0095] During the production process, if the raw material supply status changes (such as raw material shortage or transportation delay), or the construction plan at the construction site is adjusted temporarily (such as urgent demand, suspension of demand), the system recalculates the scores and weights of each factor in real time and dynamically refreshes the mixing task queue to ensure that the scheduling always conforms to the latest resource status and construction requirements, and avoid resource waste or construction site delay caused by rigid production scheduling.

[0096] Finally, through the above dynamic adjustment and optimization steps, the mixing plant realizes "flexible production", that is, the mixing plan and production schedule are no longer rigidly fixed, but are continuously adjusted elastically with the dynamic raw material supply, construction site changes and real-time demand prediction. This mechanism effectively avoids the occurrence of two extreme situations of raw material hoarding waste and resource shortage and cut-off supply, and at the same time ensures that each project order is shipped on time and the construction progress is smoothly promoted, overall improving the resource utilization rate, production flexibility and service response ability of the concrete mixing plant.

[0097] In the description of this specification, the description with reference to terms such as "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0098] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the present invention to only the specific embodiments. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An integrated management system for a concrete mixing plant, characterized in that: It includes a data acquisition unit, a demand forecasting unit, and a dynamic optimization module; Data acquisition unit: Connect to the raw material supplier system to obtain raw material supply data and concrete usage plans for different time periods; Demand forecasting unit: Incorporate meteorological information and construction site status. Based on the basic concrete usage plan, predict the post-pouring concrete demand by combining the meteorological impact coefficient and the construction site status adjustment coefficient. The expression is: , where is the predicted concrete demand, is the basic concrete usage plan, is the meteorological impact coefficient, is the construction site status adjustment coefficient, , are the weight coefficients, and ; Dynamic optimization module: Substitute the raw material supply data and the concrete usage demand result into the dynamic adjustment model. The dynamic adjustment model dynamically adjusts the mixing progress, and the expression is: , where is the adjusted production speed, is the predicted concrete usage demand, is the maximum bearable production capacity, and establish a mixing task queue to intelligently sort the production order according to the material supply status and the shipping priority.

2. The integrated management system for a concrete mixing plant according to claim 1, wherein: The dynamic optimization module receives the raw material supply data from the data acquisition unit and the concrete usage demand data output by the demand forecasting unit, synchronizes and aligns the raw material data and demand data according to the time dimension. The raw material supply data includes the current inventory level, in-transit transportation status, and estimated replenishment cycle, and the demand data includes the predicted values of concrete consumption at each construction site for corresponding time periods.

3. The integrated management system of a concrete mixing plant according to claim 2, characterized in that: The dynamic optimization module takes the raw material supply data and the concrete usage demand result as input variables and substitutes them into the dynamic adjustment model. The dynamic adjustment model dynamically calculates the maximum production capacity and production rhythm that the mixing plant can bear within each time period based on the current inventory sufficiency, transportation risk assessment, and future supply guarantee level; After the dynamic adjustment model outputs the production load curve, establish a mixing task queue according to the delivery requirements and priority requirements of different construction projects. Each mixing task corresponds to a concrete batch order; Based on the material supply situation and delivery priority, use the weighted sorting algorithm to intelligently arrange the production order. After determining the priority order of the mixing tasks, dynamically adjust the delivery time of each batch of concrete according to the predicted completion time of the mixing tasks and plan the loading order.

4. The integrated management system of a concrete mixing plant according to claim 3, characterized in that: The processing logic of the dynamic adjustment model is as follows: Obtain the sufficiency index, transportation risk coefficient, and future supply guarantee index, and calculate the maximum production capacity that the mixing plant can bear at the current stage.

5. The integrated management system of a concrete mixing plant according to claim 4, characterized in that: Calculate the maximum production capacity that the mixing plant can bear at the current stage, and the expression is: , where is the maximum production capacity that can be borne, is the nominal maximum production capacity of the mixing plant, represents the selection of the minimum value, is the adequacy index, SAI is the future supply guarantee index, and TRC is the transportation risk coefficient.

6. The integrated management system for a concrete mixing plant according to claim 5, characterized in that: The calculation logic of the sufficiency index is: Obtain the sufficiency index by dividing the current raw material inventory by the raw materials required for predicted concrete production within the corresponding time period; The calculation logic of the transportation risk coefficient is: Obtain the transportation risk coefficient by dividing the recorded transportation delay duration by the normal transportation time; The calculation logic of the future supply guarantee index is: Obtain the future supply guarantee index by dividing the recently promised delivery volume by the raw materials required for the future time period in the production plan.

7. The integrated management system of a concrete mixing plant according to claim 6, characterized in that: The demand forecasting unit introduces meteorological information, including rainfall, temperature, humidity, and wind speed, to generate a meteorological influence coefficient; Connect to the construction site status data, including the actual construction progress, construction team work arrangements, and on-site construction surface status, to generate a construction site status adjustment coefficient.

8. An integrated management system for a concrete mixing plant according to claim 7, characterized in that: The calculation of the construction site status adjustment coefficient includes the following steps: Obtain the construction progress deviation by subtracting the construction plan progress from the actual completed progress, and obtain the work surface deviation by subtracting the expected work surface ratio from the actual available work surface ratio on-site; Normalize the construction progress deviation and the work surface deviation so that the value ranges of the construction progress deviation and the work surface deviation are mapped to between [0,1] to obtain the normalized value of the construction progress deviation and the normalized value of the work surface deviation; Sum the normalized value of the construction progress deviation and the normalized value of the work surface deviation to obtain the construction site status adjustment coefficient.

9. The integrated management system for a concrete mixing plant according to claim 8, wherein: The calculation of the meteorological influence coefficient includes the following steps: Set the rainfall influence weight according to the rainfall probability and expected rainfall in the weather forecast, and calculate to obtain the rainfall factor; Obtain the highest temperature on the prediction day, set the weight of the high-temperature impact, obtain the high-temperature factor, and if the meteorological department issues a severe convective weather alert or a red rainstorm warning, obtain the comprehensive meteorological alert factor; The meteorological impact coefficient is obtained by adding the rainfall factor, the high-temperature factor, and the comprehensive meteorological alert factor.

10. A comprehensive management system for a concrete mixing plant according to claim 9, characterized in that: The data acquisition unit docks with the raw material supplier system to collect the supply data of raw materials in real time, including obtaining the current inventory quantity of various raw materials, the in-transit transportation status of raw materials, the estimated arrival time, and the supply cycle information; Link and access the construction project management system to obtain the concrete usage plan for different construction stages, including the specific demand for concrete in each future time period, the demand time period, and the corresponding engineering project number.

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