159 results about "Cost control" patented technology

The invention relates to the technical field of project cost management, in particular to a project cost-oriented information management method and system, and the method comprises the following steps: carrying out multi-source data collection and standardization processing, carrying out the automatic calculation, logic verification and correction of a project amount based on an AI calculation amount engine and a rule engine, and generating a precise project amount list; calling a dynamic pricing model, carrying out deviation analysis on the actual cost and the plan cost based on a earned value analysis method and a machine learning model, predicting the cost hyper-branched risk, and carrying out graded early warning; constructing a multi-participant collaborative platform, and supporting change application submission, associated cost influence calculation, online examination and approval, problem tracking and progress synchronization; the whole-cycle data is classified and archived, an enterprise-level cost index library is generated based on historical project data, cost reference is provided for a new project, and the method is suitable for cost information efficient management and cost control of the whole life cycle of constructional engineering, municipal engineering, installation engineering and the like.

The invention relates to the technical field of construction industry project cost, and provides a project cost management system based on big data, the core of the system is to integrate a big data technology and comprehensively manage project cost, data management covers links of acquisition, storage, analysis and maintenance, data quality and safety are ensured, and a foundation is built for cost management; the accurate cost analysis uses multiple algorithm models to deeply mine data association, so that accurate prediction and fluctuation reason analysis are realized, and cost optimization is assisted; the efficient business logic layer and the user interaction layer cooperatively operate, the business function is complete, the process is smooth, the interface is friendly, the visualization is strong, and a feedback channel is arranged to promote optimization; data acquisition is wide, storage is efficient, and the method is far better than a traditional scheme; the analysis depth and the visualization effect are prominent, and a more valuable decision basis is provided; the system is complete in business function and scientific in management, improves enterprise cost control and decision-making capability, and is good in user experience and high in safety.

The invention discloses an order-driven cross-factory collaborative production system, and relates to the technical field of intelligent manufacturing and supply chain collaboration, and the system obtains the productivity data, logistics cost and tax policies of a plurality of production bases such as Ningbo, Thailand and America in real time, and carries out the intelligent splitting and distribution of orders through a multi-base productivity game algorithm. And dynamic optimal matching of the order and the productivity is realized. Meanwhile, the system integrates WMS inventory data and third-party logistics real-time quotation, a transportation scheme with the lowest total cost is generated by adopting a genetic algorithm, and cross-border logistics and tax expenditure are remarkably reduced. The system overcomes the problems of information isolated island, response lag, extensive cost control and the like in traditional multi-factory production, realizes global productivity collaborative optimization and supply chain integrated intelligent decision, and improves the enterprise order performance efficiency and the overall resource utilization rate.

The invention relates to the technical field of engineering cost dynamic measurement and calculation, in particular to an intelligent engineering cost dynamic measurement and calculation and cost control method and system. Comprehensive influence factors of nodes can be extracted from a complex construction task incidence relation through a graph convolutional network; comprising resource intensity, progress sequence and potential resource conflict problems, so that accurate identification of key construction paths is improved, the real-time feedback capability of project progress and cost is enhanced, dependence of a traditional budget model on static factors is effectively avoided, project decision is optimized according to real-time changes, and the construction efficiency is improved. The efficient distribution of budget and resources is ensured, through the application of the non-dominated sorting genetic algorithm, and according to the residual budget, the construction period and the resource value, comprehensive evaluation and node screening optimization are carried out, so that project management can flexibly adjust the budget and the construction period based on the actual situation, the situation of unreasonable fund scheduling or resource waste is avoided, and the project management efficiency is improved. And the accuracy and flexibility of engineering project management are improved.

The invention relates to the technical field of project cost management, in particular to a hydraulic engineering construction cost control system and method, and the system comprises a material consumption analysis module, an inventory early warning calculation module, a dynamic inventory adjustment module, a replenishment trigger optimization module, and a consumption stability evaluation module. According to the method, the material consumption rate is dynamically monitored, the construction progress and engineering quantity are combined to measure and calculate data, a consumption trend curve is established, the actual use condition is compared, the consumption rate deviation is accurately quantified, real-time evaluation of material use is achieved, the number of supply days is calculated in combination with inventory data, the replenishment period is matched, and the replenishment time is dynamically adjusted; the inventory level is optimized, fund occupation is reduced, the stability is evaluated according to the consumption fluctuation range, the maximum consumption fluctuation value is calculated, the demand is adjusted in combination with replenishment, the inventory early warning threshold value is dynamically corrected, the supply chain breakage risk is reduced, the adaptability of construction material management is improved, and the cost control accuracy is improved.

The invention is suitable for the technical field of cost control, and provides a cost control method and system, and the system comprises a data collection and integration module, a geological change detection module, a geological risk prediction module, and a cost influence evaluation module. According to the method, through real-time data acquisition, historical data integration and dynamic prediction, the scientificity and accuracy of construction cost management are remarkably improved. A weighted interpolation method is utilized to predict a geological parameter trend, a historical risk mode and real-time dynamic change are combined, a risk occurrence probability and a construction influence index are scientifically quantified, a high-risk area is determined through priority ranking, resource allocation is optimized, and therefore construction time and economic cost are effectively reduced. By dynamically optimizing the construction scheme and resource allocation, the method realizes the flexibility and high efficiency of the construction process, and avoids delay and waste caused by risk response lag in traditional construction.

The invention relates to the technical field of project accounting, in particular to a small and medium-sized enterprise single-project accounting method based on a business financial minimum data unit, which comprises the following steps of: matching collection and fulfillment nodes, distributing account affiliation, marking change of difference between income and expenditure directions, generating a cash flow recursion path, and uniformly writing in details of a total classification account to obtain accounting chain structure data. According to the method, time matching and amount identification of project collection information are realized by mapping contract node amounts and actual collection data in sequence, a node amount association chain with clear affiliation is constructed in combination with a mode of matching receivable nodes with account amounts step by step, and a linkage judgment mechanism of voucher numbers and revenue and expenditure identification is matched; according to the method, the income and expenditure directions of each stage of the project are distinguished, the fund change trajectory is reflected by sequence number difference operation, the directions of positive and negative items of cash flow are clear, and the response speed and accuracy of single-project accounting in dynamic fund tracking, cost control and accounting concentration are effectively improved.

The invention relates to the field of catering management, in particular to a healthy diet-based catering management method, which comprises the following steps of: acquiring and integrating user information, acquiring user diet basic information, distributing a monitoring period and continuously observing the dynamic change of the user diet basic information to provide a basis for subsequently generating a diet scheme; by generating the initial recipe, processing to obtain the personalized recipe and optimizing the recipe recommendation strategy, the diet plan is ensured to be closer to the actual demand of the user, and the user experience is improved; according to the optimized recipe recommendation strategy, an intelligent diet scheme is evaluated, accurate tracking of food materials and intelligent dish matching are carried out, and the accuracy and controllability of cooking are improved; the financial information of the restaurant is analyzed, the cost control is optimized, the operation cost of the restaurant is reduced, the profitability is improved, and a powerful guarantee is provided for sustainable development of the restaurant. The method is used for solving the technical problem that the current catering management efficiency is not high.

The invention relates to the technical field of cost management, in particular to an enterprise cost control method and system based on big data, and the method comprises the following steps: detecting the calling record and use frequency of enterprise business resources, and recognizing key fund inflow and outflow nodes according to the flow direction frequency of a fund flow path to obtain cost classification boundary data. According to the invention, dynamic management and optimization of real-time cost data are realized through comprehensive analysis of enterprise resource calling data and fund flow direction, and tracking accuracy of resource utilization is improved through real-time monitoring of calling frequency and fund flow direction of service nodes, so that a cost control process is more transparent and predictable. According to the method, the cost items can be dynamically matched and optimized by using the time stamp and the related data of the fund flow, the accurate adjustment of the cost control is realized, in addition, the introduction of the dynamic cost distribution index allows the enterprise to quickly respond in the changing market environment, and the cost management error caused by the market fluctuation is effectively reduced.

The invention discloses an electric power remote cost control decision-making method and system, particularly relates to the technical field of intelligent power grids, and is used for solving the problem that electric power remote cost control management is not clear. According to the method, the power consumption behavior, the payment record, the external credit information and the environmental data of the user are collected, the power consumption and payment characteristics of the user are accurately extracted in combination with data preprocessing and tagging modeling, the user behavior characteristic matrix is generated by using the sliding window strategy, and the user risk is dynamically evaluated in combination with the time sequence model and the static classification model. The method comprises the following steps: acquiring a risk score of a user, outputting an accurate risk score, generating a user comprehensive risk grading result based on the risk score, electricity utilization importance and a defaulting accumulated score, formulating a differentiated fee control strategy for different users, dynamically capturing fee control evaluation information by analyzing seasonal fluctuation of electricity utilization and fee payment capabilities of the users, and generating an optimization signal. Dynamic adjustment of the charge control strategy is realized, the flexibility of charge control management of an electric power company is improved, and both economic benefits and user experience are taken into account.

The invention discloses a discrete manufacturing enterprise product cost accounting method, and belongs to the technical field of commercial data processing, and the method comprises the steps: dividing the production process of each part in a product into a plurality of production processes; according to the inflow cost and the material picking cost of one production process, the in-process cost, the waste product cost and the completion cost of the production process are obtained through the processing motivation in the production process, and the inflow cost of the next production process is determined according to the completion cost; through circulation of the completion cost between continuous production processes, the completion cost of each part is obtained, so that the product cost is obtained. According to the method, the part production procedures are divided, cost circulation is carried out, refined cost control is achieved, cost accounting is independently carried out in each procedure, and data are accurate. By reasonably sharing the manufacturing cost and the waste cost, the cost transfer of cross-workshop circulation is simplified, and the cost accounting accuracy is improved.

The invention belongs to the technical field of IT type project cost financial management, and discloses an IT type project cost financial independent accounting system, which comprises a project management module, a receivable management module, a payable management module, a purchase management module, a financial system data exchange module, a human resource data exchange module and an early warning management module. According to the system, integrated management is adopted, project cost is monitored in real time and dynamically adjusted, the system collects and updates cost data in real time, rapid adjustment is carried out once deviation is found, it is ensured that the cost is controlled within a prediction range, project management flexibility and response speed are improved, cost hyper-branched risks are reduced, and meanwhile through automatic data processing and accounting processes, the project management efficiency is improved. The cost accounting accuracy and efficiency are remarkably improved, personal errors are avoided, manual calculation is simplified, a project manager can efficiently master the cost condition, powerful data support is provided for project decision making, and the scientificity and effectiveness of project management are ensured.

The invention discloses a high-frequency vibration absorption fastener design method for restraining local bending mode vibration of a steel rail. The method comprises the following steps that a finite element analysis model of the steel rail is established according to the set length and steel rail parameters, a rail model under the harmonic excitation condition is established, and a relational expression met by the overall rigidity and damping of a double-layer fastener model is established; constructing a kinetic equation of vertical movement of the iron base plate; constructing a target optimization function for designing the track fastener system based on the error; and constructing a cost model of the fastener in the production process, optimizing cost control of fastener design, outputting the quality of the iron base plate, the rigidity of the upper layer structure and the rigidity of the lower layer structure under the optimal cost control, and designing the fastener system. According to the method, high-feasibility solutions are provided for relieving local bending modal vibration of the steel rail, high-order polygons of wheels and corrugation of the steel rail.

The invention relates to the technical field of system dynamics, and discloses an electricity certificate carbon market price analysis method and system based on system dynamics, and the method comprises the steps: S1, determining the main body of a green certificate transaction market and the main body of a carbon emission permit transaction market, and determining a renewable energy power generation mode; s2, constructing a TCC cost control mechanism; s3, TCC cost is calculated according to a TCC cost control mechanism; s4, establishing stock flow dynamic model frames of the green certificate market and the electricity market and the carbon emission permit trading market and the electricity market, and combining the two dynamic model frames to generate an electricity certificate carbon market stock flow dynamic model frame; and S5, analyzing the electricity evidence carbon market price. The system comprises an information input unit, a mechanism construction unit, a calculation and analysis unit and a system dynamics model framework construction unit. According to the method, the system dynamics and the method for controlling and optimizing the TCC cost are combined, and the analysis accuracy and reliability are improved.

The invention relates to a self-learning algorithm for collecting the quality of a field communication network, which is based on an Actor-Critic algorithm and QoS (Quality of Service) evaluation, realizes strategy learning and value evaluation by collecting multi-dimensional QoS data in real time and utilizing a neural network, and optimizes network selection in a long term, and comprises the following processes: data collection and preprocessing; carrying out model training based on Actor-Critic; a decision execution and feedback optimization mechanism; and performing energy consumption management and switching cost control. According to the method, the Actor-Critic learning algorithm and QoS evaluation are taken as a reward function, a switching cost penalty mechanism is introduced, the network quality is comprehensively evaluated, accurate switching is realized, unnecessary switching is reduced, the network stability is improved, the equipment can adapt to environment change and optimize a switching strategy, the switching strategy is automatically adjusted according to network characteristics in different time periods, and the network quality is improved. And a historical data optimization long-term strategy is adopted, and a power consumption factor is introduced, so that low-power-consumption intelligent switching is realized, the endurance time of the equipment is prolonged, and the communication reliability and stability of the network equipment are improved.

The utility model provides a refrigerant filling machine to solve the problem that in the prior art, a large amount of manpower and time cost are consumed for achieving high-precision filling. The refrigerant filling machine comprises a booster pump, a storage tank, an electronic scale, a control system, a filling pipeline, a pressure sensor, a roller and a storage chip. The refrigerant filling machine is excellent in cost control, traditional complex assemblies are abandoned, the booster pump and the high-precision online electronic scale are combined, and the manufacturing, debugging and maintaining cost is reduced. The electronic scale monitors the weight in real time, the control system performs comparison operation, and the error of the filling amount is controlled within five thousandths. The whole filling process is automatically executed by a control system, and an operator only needs to simply set parameters and start operation to complete a refrigerant filling task. The outer wall of the storage tank is connected with an external power supply through the leakage protector, the power supply is automatically cut off during leakage, and the alarm sends out a signal during abnormity.

The invention relates to the technical field of international trade logistics path planning, in particular to an international trade logistics path planning method and system based on multi-dimensional data. According to the method, multi-dimensional data such as policies and regulations, economic stability, market opening degree and infrastructure construction are comprehensively considered, the trade convenience and trade stability of a trade country can be more comprehensively evaluated, logistics path planning is more accurate and scientific through comprehensive consideration of the multi-dimensional data, and the logistics path planning efficiency is improved. One-sidedness and misleading possibly caused by single-dimension data are effectively avoided, so that a better international trade logistics path is planned, the risk of international trade is reduced, and the international competitiveness of an enterprise is improved; the technical problem that the optimal logistics efficiency and cost control cannot be realized possibly because the complexity and diversity of political economic environments of different countries are not fully considered in the design and planning of logistics paths in the process of international trade activities at present is solved.

The invention discloses a whole-process project cost consultation management system. According to the invention, the budgeting module realizes fine management of budgeting through an internal refining sub-module. The data acquisition sub-module ensures the real-time performance and accuracy of budget data, and avoids errors and delay of traditional manual input. The budget modeling sub-module establishes a scientific budget model by using historical data and algorithms, and improves the prediction accuracy of budget. The intelligent recommendation sub-module provides intelligent suggestions for budgeting based on a collaborative filtering algorithm, assists manual decision making, and reduces human errors. The dynamic adjustment sub-module adjusts the budget in real time according to the market change and the project progress, and ensures that the budget conforms to the actual situation. Through cooperative work of the sub-modules, the accuracy and efficiency of budgeting are greatly improved, and a solid foundation is laid for cost control and fund management of a project.

The invention relates to a user behavior fused flow casting dynamic pricing method and device, equipment and a medium. The method comprises the steps of obtaining an original behavior log of a user, performing feature extraction processing on the original behavior log, generating a structured behavior feature vector, performing quantification processing on the structured behavior feature vector, and generating a user-level behavior willingness index; historical transaction data is obtained, the user-level behavior willingness index and the historical transaction data are input into a price elasticity prediction model for processing, a user-level real-time price elasticity coefficient is output, and the price elasticity prediction model is constructed based on a random forest algorithm and a gradient boosting algorithm; and performing dynamic bidding calculation processing based on the user-level real-time price elasticity coefficient and a basic bidding parameter preset by the advertiser to generate a final optimized bidding. According to the method, user behavior feature analysis, price elasticity prediction and dynamic bidding calculation are fused, individuation of flow casting dynamic pricing is achieved, the rate of return on investment of advertisement putting is effectively increased, and cost control is optimized.

The invention discloses a multi-objective optimization decision-making method and system for sewage treatment based on OLAP reinforcement learning, and solves the problems that an existing sewage treatment control method neglects carbon emission, is extensive in cost control and does not integrate a carbon transaction mechanism. The method comprises the following steps: constructing an OLAP cube, and generating an optimal historical strategy set; establishing a state set according to the sewage environment parameters and the carbon price; an action set is established according to the optimal historical strategy set, and an action priority strategy is set according to the carbon emission weight partition; establishing a multi-target reward function dynamically adjusted according to the carbon price; constructing each controller agent model for training until the strategy converges; and dynamically outputting an optimal strategy by the intelligent agent according to the change of the carbon price. According to the method, a multi-dimensional OLAP cube is constructed to analyze the incidence relation between key variables, a plurality of process control agents are constructed, reinforcement learning collaborative optimization of working condition adjustment is achieved, the carbon emission item optimization weight is adjusted according to the real-time carbon transaction price, and dynamic policy adaptation is achieved.

The invention discloses a full-link coverage logistics optimization method, which comprises a goods picking step and a goods allocation step, and the goods picking step comprises a goods taking mode judgment step which comprises a whole vehicle transportation mode and a circulating goods taking mode; and when the goods taking mode is a circulating goods taking mode, determining a goods taking transportation path and a loading scheme, determining the loading scheme comprises determining a loading sequence and determining a loading position, and the goods taking transportation path comprises paths between suppliers and between the suppliers and goods picking bins. According to the full-link coverage logistics optimization method, multi-customer, multi-cargo-warehouse and multi-supplier order demands are considered, joint optimization is carried out on an existing path planning system in three links of front-end cargo picking, trunk transportation and turnover appliance management, the efficiency and cost control capability of automobile logistics are comprehensively improved, transportation resources are reasonably scheduled, and the transportation efficiency is improved. And the logistics cost is reduced.

The invention relates to the technical field of inventory optimization, and discloses a retail inventory optimization method based on full-link management, which comprises the following steps: collecting historical data to construct a full-link graph structure, and predicting the sales demand of each node in a future period based on a graph convolutional network and a time sequence model; acquiring real-time data of each link in a whole link, and determining an initial safety stock, a replenishment period and an order quantity based on the whole link graph structure and in combination with the sales demand data; and based on an inventory optimization algorithm, iteratively solving the optimal safe inventory, the replenishment cycle and the order quantity, and executing an inventory optimization operation according to an optimization result. According to the method, the graph convolutional network and the quantum optimization algorithm are innovatively combined, dynamic inventory optimization based on full-link management is realized, the intelligent level of inventory management is improved, and the method has remarkable advantages in precision, response speed and cost control; a brand-new and efficient inventory optimization solution is provided for retail enterprises.

The invention belongs to the field of enterprise resource planning (ERP) systems and cost accounting, and particularly relates to a data chain construction method and system for supporting product material cost accounting based on project numbers, and the method comprises the steps: S1, generating a to-be-delivered product project number according to an order; s2, constructing an order-production plan relation mode; s3, constructing a production plan-purchase order relation mode; s4, constructing a purchase order-inventory relation mode; s5, constructing a production plan-material picking list relation mode; s6, constructing an order-delivery order relation mode; step S7, constructing an order-settlement order relation mode; according to the method, key data breakpoints are connected in series to support full-process material cost accounting, each direct material cost quota and actual cost expenditure are accurately tracked, finally, refined cost control is achieved, and decision-making quality is improved.

The invention belongs to the technical field of constructional engineering, and particularly relates to a self-adaptive constructional engineering cost control method and system. A load sensor installed on a tower crane is used for monitoring the weight of a hoisted material, the number of hoisting times is combined, the real-time using amount of the material is calculated through a formula, and a big data analysis technology and a machine learning algorithm are used for constructing a cost prediction model. Factors such as manual efficiency change coefficients at different construction stages, shutdown time length caused by abnormal weather and additional cost coefficients caused by the shutdown time length are considered, and the cost change trend can be accurately reflected; the problems that a traditional construction engineering cost control method cannot adapt to various uncertain factors in engineering, so that cost prediction is not accurate, and coping strategies are lacked are solved, cost hyper-branched and resource waste are prevented, and the problems of accurate control and efficient management of cost are solved.

The invention specifically relates to a BIM and big data analysis-based construction project construction cost control method, and relates to the technical field of construction project construction management. Cost budgeting and prediction; coordinated management and control of progress resources; cost monitoring and early warning; and collaborative management and system guarantee are realized. According to the method, the BIM model, the Internet of Things and the external data source are integrated, the standardized cost database is constructed, and the accuracy and the real-time performance of the data are ensured; automatically counting the engineering quantity by using a parameterized family library, and predicting a material price trend in combination with an LSTM model in a cost budgeting and predicting stage; generating a cost risk thermodynamic diagram through Monte Carlo simulation, and quantifying the risk probability of each node; meanwhile, indexes such as BCWS and BCWP are calculated in real time based on earned value management, automatic early warning and reason analysis are performed when cost deviation occurs, accurate cost control of the whole process from estimation to budget to construction is achieved, and the cost hyper-branched risk is effectively avoided.

The invention belongs to the technical field of aircraft test design, and particularly relates to a method and a device for determining risks of a manufacturer and an ordering party in a testability test. The method comprises the following steps: step S1, obtaining influence factors of a contractor risk and an ordering party risk; s2, calculating the maximum feature root of a first matrix constructed by the importance among the influence factors, and meanwhile, calculating the maximum feature root of a second matrix constructed by the influence degrees of the influence factors on the acceptor and the ordering party; s3, calculating a correction amount according to a ratio of the maximum feature root of the first matrix to the maximum feature root of the second matrix; and S4, according to the correction amount, correcting a given acceptor risk and a given ordering party risk. According to the method, the design requirements of the acceptor risk and the ordering party risk are met, and scientific balance between cost control and risk prevention and control is realized.

The invention discloses an intelligent construction cost control method and system, and relates to the technical field of cost control, and the system comprises a construction detection end, a cost prediction end and an influence scheduling end. The construction detection end is used for formulating a planning scheme of a construction project and timely judging whether the construction cost in different periods is abnormal or not; the cost prediction terminal predicts whether construction stagnation occurs in advance; and the influence scheduling end is used for performing abnormal scheduling and complementing on the construction cost of the project cost in real time through the planning scheme of the construction project when construction delay or construction stagnation occurs, and adjusting the construction decision of the planning scheme in time. According to the intelligent construction cost control method and system, real-time control and abnormity judgment are carried out on the cost planning of the whole life cycle of the project in time, whether the construction time is prolonged or not is predicted according to the influence of the environment on construction, and abnormity scheduling and complementing can be carried out on the construction cost of the project in time.

This invention belongs to the field of coal procurement technology, and relates to a procurement decision-making method and system based on multi-timescale coal demand forecasting. It includes: acquiring power generation influencing factor data at at least two time scales, and generating power generation forecast values ​​corresponding to each time scale based on the power generation influencing factor data; fusing the power generation forecast values ​​at each time scale to obtain a fused power generation forecast value; decomposing the fused power generation forecast value into initial demand quantities for different coal types according to the consumption rate of each generating unit for different coal types, and adjusting the initial demand quantities according to a preset blending strategy to obtain the target demand quantity for each coal type; acquiring coal price time series data for each coal type, and generating future coal price forecast values ​​for each coal type based on the coal price time series data; and determining a procurement decision scheme based on the target demand quantity for each coal type and the coal price forecast value. This invention achieves accurate decision-making and cost control in fuel procurement.

This invention relates to the field of power system demand response technology, and provides a user demand response method based on master-slave game theory under cost control constraints. The method includes: establishing a demand response model using master-slave game theory, where electricity retailers design time-of-use pricing strategies, and electricity users respond based on a convex utility function; the utility function includes a quantification term for electricity usage satisfaction and a calculation term for electricity costs; the electricity retailers' revenue function includes four functions: user electricity costs, long-term market electricity purchase costs, current market electricity purchase costs, and conditional risk value, coupled with the characteristics of the electricity spot market and risk management requirements; proving the existence of a Nash equilibrium solution using backward induction; and optimizing the strategy based on a slime mold optimization algorithm. This invention provides important support for electricity retailers to formulate flexible pricing mechanisms and tap demand-side resources in terms of cost control for users with high response potential and optimization of peak-valley load differences.

This invention relates to the field of garment production chain collaboration, specifically disclosing a method for querying and quoting garment styles based on the SKU dimension. The method includes: creating and distributing query forms supporting multi-dimensional selection by style, style color, and style color code SKU; the supplier terminal generating a quotation based on the query form, calling its internal standard component cost library to calculate details for SKU entries, updating the status to "quoted" and generating a unique version record after confirmation; the brand performing operations such as accepting or rejecting the quotation; and after order completion, using actual production cost data to calibrate the supplier's standard cost library. This invention achieves refined cost control from the style level to the SKU level, ensures the rigor and traceability of the collaborative process through a versioned state machine, and realizes self-optimization of the cost model through a data closed loop of quotation-production-calibration, significantly improving the collaborative efficiency and cost control capabilities of the garment supply chain.