Supply chain multi-party sharing management system based on digital transaction platform

Abstract

The invention discloses a supply chain multi-party sharing management system based on a digital transaction platform, and relates to the technical field of supply chain management systems. The supply chain management platform is in communication connection with a data acquisition and integration module, a prediction analysis module, a resource scheduling module, a collaborative operation module and a monitoring optimization module, and all the modules are in electric signal connection. According to the supply chain multi-party sharing management system based on the digital transaction platform, resource allocation is dynamically adjusted by using a resource scheduling demand prediction result in combination with a current resource condition, resources are ensured to be effectively utilized at correct time and places, the resource utilization efficiency is remarkably improved through dynamic adjustment and configuration optimization capabilities, and the resource utilization rate is improved. According to the method, resource waste is reduced, market changes can be quickly adapted, emergency demands can be responded, and a quantitative evaluation tool is provided for resource scheduling by using the resource scheduling evaluation index, so that various resources in a supply chain are intelligently allocated and optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain management systems, and in particular to a supply chain multi-party sharing management system based on a digital transaction platform. Background Art

[0002] With the deepening of global economicization and the rapid development of information technology, competition among enterprises has shifted from single product competition to competition in overall supply chain efficiency and service level. The advancement of information technology, especially the widespread application of cloud computing, big data, the Internet of Things, artificial intelligence and other technologies, has provided strong technical support for the digitalization and intelligence of supply chain management. Against the background of increasingly refined global division of labor, supply chain management has become more and more complex. There are many participants in the supply chain, including suppliers, manufacturers, distributors, retailers, etc. Information sharing and collaborative cooperation among all participants are crucial to improving the overall efficiency of the supply chain. As a new type of supply chain management tool, the digital trading platform has the advantages of information integration and sharing as well as process optimization and collaboration, which helps to improve the overall efficiency of the supply chain.

[0003] In supply chain management, since resource scheduling and allocation often involve multiple goals and there are certain conflicts between different goals, the resource scheduling and allocation problem becomes more complicated. Therefore, how to evaluate the resource scheduling and allocation of the supply chain management process and realize dynamic adjustment and allocation of resource scheduling based on the resource scheduling effect is the problem we need to solve. To this end, a supply chain multi-party sharing management system based on a digital trading platform is proposed. Summary of the invention

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: A supply chain multi-party sharing management system based on a digital transaction platform, including a supply chain management platform, wherein the supply chain management platform is communicatively connected with a data collection and integration module, a prediction and analysis module, a resource scheduling module, a collaborative operation module, and a monitoring and optimization module, wherein the modules are connected by electrical signals;

[0005] The data collection and integration module is used to collect multi-source supply chain data from various supply chain participants, including inventory, production progress and sales data, and pre-process and integrate the collected multi-source supply chain data, wherein the supply chain participants include suppliers, manufacturers and distributors;

[0006] The forecasting and analysis module is used to perform demand analysis on supply chain data, extract forecasting features of the supply chain's production-demand ratio, production-sales ratio, sales growth rate, inventory turnover rate, and safety inventory, traverse relevant data of the forecasting features, obtain a supply chain forecasting feature table, and build a supply chain scheduling forecasting model based on machine learning technology, conduct forecasting and analysis on the supply chain's resource demand, sales trends, and inventory changes, and evaluate the resource scheduling effect;

[0007] The resource scheduling module is used to coordinate the resource flow of each link of the supply chain according to the prediction results and the current resource status, ensure that resources are reasonably used at the right time and the right place, realize dynamic adjustment and optimal allocation of resources, and improve resource utilization efficiency;

[0008] The collaborative operation module is used to promote collaborative operations and information sharing among all parties involved in the supply chain, provide online collaborative tools, support real-time communication and collaboration among multiple parties, coordinate and resolve problems and conflicts encountered in collaborative operations, and improve the response speed and flexibility of the entire supply chain;

[0009] The monitoring and optimization module is used to monitor the overall process of supply chain management and continuously optimize and upgrade the system based on actual operating conditions and user feedback.

[0010] Preferably, the data acquisition and integration module includes a data collection unit, a preprocessing unit and a data integration unit;

[0011] The data collection unit is used to identify the types of supply chain data to be collected and to establish a data interface to collect supply chain data;

[0012] The preprocessing unit is used to preprocess the collected data, and the preprocessing process includes cleaning, sorting and standardization to ensure data quality and consistency;

[0013] The data integration unit is used to integrate the pre-processed multi-source supply chain data, and prioritize the resources to be scheduled according to the importance of the supply chain resource scheduling process, obtain a resource scheduling sequence list, form a global view of the supply chain, and provide a basis for subsequent analysis and prediction.

[0014] Preferably, in the data collection and integration module, the process of preprocessing and integrating the collected multi-source supply chain data includes:

[0015] Clearly define the types of supply chain data that need to be collected from each supply chain participant, namely inventory, production progress, and sales data, and establish a unified data interface and transmission protocol to identify each supply chain participant, namely suppliers, manufacturers, and distributors, to ensure that data can be transmitted smoothly and securely. Inventory includes raw material inventory, work-in-progress inventory, finished product inventory, etc. Production progress includes production plan, actual production volume, production delays, etc. Sales data includes order volume, sales volume, sales revenue, return volume, etc.;

[0016] Use ETL tools to extract the required data from the data sources of each supply chain participant, collect the multi-source supply chain data of each participant, and transfer the extracted data to the data warehouse. When extracting data, it is necessary to ensure the integrity and accuracy of the data to avoid omissions or errors. The data sources of each supply chain participant are ERP system, CRM system, and database;

[0017] Preprocessing the collected data by cleaning to remove duplicate data, process missing values, correct erroneous data, etc., helps improve the quality and accuracy of the data, provides a reliable basis for subsequent analysis and prediction, and converts data from different sources and formats into a unified format and standard so that it can be easily processed in the subsequent data integration and analysis process;

[0018] Classify the pre-processed supply chain data according to the supply chain data type, associate data from different sources, and fuse the associated data to integrate inventory data, production progress data, sales data, etc., so as to fully understand the operation of the supply chain;

[0019] Based on the integrated supply chain data, the resource demand in the supply chain is analyzed, and the resources to be scheduled are prioritized and the resource scheduling sequence is determined according to the importance and urgency of the resource scheduling process;

[0020] Based on the results of the priority division, a resource scheduling sequence table is generated to clarify the scheduling order and priority of each resource. Based on the integrated data and the resource scheduling sequence table, a global view of the supply chain is constructed to display each link, participant, resource flow, etc. of the supply chain, so as to fully understand the operating status and potential problems of the supply chain.

[0021] Preferably, in the prediction and analysis module, the process of evaluating the resource scheduling effect includes:

[0022] Traverse the pre-processed inventory, production progress and sales data collected from all supply chain participants, conduct demand analysis, and extract the associated prediction features of the supply chain forecast, which are the production-demand ratio, production-sales ratio, sales growth rate, inventory turnover rate and safety stock. The production-demand ratio reflects the ratio of the number of products produced by the enterprise to the demand of its users for the product. It is an important indicator to measure the degree of matching between production and sales. The production-sales ratio is similar to the production-demand ratio, but focuses more on the sales link, reflecting the market acceptance and sales efficiency of the enterprise's products. The sales growth rate represents the growth of sales volume and is an important indicator for evaluating market potential and enterprise growth capabilities. The inventory turnover rate reflects the speed of inventory turnover and is a key indicator to measure inventory management efficiency. The safety stock is the inventory set to ensure the stability of the supply chain, used to cope with sudden demand or supply disruptions.

[0023] Combine each forecast feature with the pre-processed inventory, production schedule, and sales data to integrate the forecast feature related data and obtain the supply chain forecast feature table;

[0024] The historical data of each prediction feature in the supply chain prediction feature table is divided into a training set and a test set. The training set data is combined with machine learning technology to build a supply chain scheduling prediction model, and the test set data is used to test the supply chain scheduling prediction model. The supply chain scheduling prediction model is built based on a linear regression model.

[0025] Combining the resource scheduling sequence table, prediction feature data and supply chain scheduling prediction model, the resource scheduling evaluation index is obtained, and different scheduling levels are set according to the resource scheduling evaluation index, namely, excellent scheduling level, medium scheduling level and poor scheduling level, and corresponding evaluation thresholds are set for each scheduling level;

[0026] Based on the resource scheduling evaluation index and supply chain scheduling forecasting model, the supply chain resource demand, sales trend and inventory changes are predicted and analyzed to determine the scheduling level and evaluate the quality of the current resource scheduling effect.

[0027] Preferably, the process of obtaining the resource scheduling evaluation index includes:

[0028] Calculate the resource demand satisfaction index based on the resource scheduling sequence table and the predicted resource demand, and preset the standard value Std of the resource demand satisfaction index D , calculate the resource demand satisfaction index adjustment value, analyze the change trend of resource demand, and the expression of the resource demand satisfaction index is: D r is the resource demand satisfaction index, D is the actual resource demand, is the predicted resource demand output by the model, D a is the actual amount of resources allocated, D rThe larger the value of, the higher the resource demand satisfaction;

[0029] Analyze the consistency between actual sales and predicted sales trends, calculate the sales trend matching index, and preset the standard value Std of the sales trend matching index S , calculate the sales trend matching index adjustment value, analyze the degree of sales trend matching index relative to the reference value, and the expression of the sales trend matching index is: S t is the sales trend matching index, S is the actual sales volume, is the predicted sales volume output by the model, S t The larger the value of, the higher the sales trend match;

[0030] Evaluate the management effect of inventory turnover rate and safety stock, calculate the inventory change control index, and preset the standard value Std of the inventory change control index I , calculate the inventory change control index adjustment value, analyze the inventory change control effect, the expression of the inventory change control index is: I c is the inventory change control index, ITO is the actual inventory turnover rate, and ITO t is the target inventory turnover rate, SI is the safety stock, SI op is the optimal safety stock, α and β are weight factors used to adjust the impact of inventory turnover rate and safety stock on the overall evaluation;

[0031] Combining the resource demand satisfaction index, sales trend matching index, inventory change control index and their corresponding adjustment values, a weighted calculation is performed to obtain the resource scheduling evaluation index, and the scheduling effect is analyzed.

[0032] Preferably, the resource demand satisfaction index adjustment value is expressed as:

[0033]

[0034] Among them, Ad D is the resource demand satisfaction index adjustment value, D r is the resource demand satisfaction index, Std D is the standard value of resource demand satisfaction index, Ad D The value of is between 0 and 1, 0 means completely unsatisfied and 1 means completely satisfied;

[0035] The expression of the sales trend matching index adjustment value is:

[0036]

[0037] Among them, Ad S is the sales trend matching index adjustment value, St is the sales trend matching index, Std S is the standard value of the sales trend matching index, Ad S The value is between 0 and 1, 0 means no match at all, 1 means a perfect match;

[0038] The expression of the inventory change control index adjustment value is:

[0039]

[0040] Among them, Ad I is the inventory change control index adjustment value, I c is the inventory change control index, Std I is the standard value of the inventory change control index, Ad I The value of is between 0 and 1, where 0 indicates extremely poor inventory control and 1 indicates perfect inventory control.

[0041] Preferably, the resource scheduling evaluation index is expressed as:

[0042]

[0043] Among them, RI is the resource scheduling evaluation index, Ad D is the resource demand satisfaction index adjustment value, Std D is the standard value of the sales trend matching index, w D is the weight coefficient of resource demand satisfaction, Ad S is the inventory change control index adjustment value, Std S is the standard value of the sales trend matching index, w S is the weight coefficient of inventory change control, Ad I is the inventory change control index adjustment value, Std I is the standard value of the inventory change control index, w I is the weight coefficient for inventory change control.

[0044] Preferably, the plurality of scheduling levels correspond to the plurality of evaluation thresholds, wherein the evaluation thresholds include an upper threshold and a lower threshold;

[0045] The multiple scheduling levels and the multiple evaluation thresholds satisfy the following relationship:

[0046] Excellent scheduling level 0<RI <RI M ; The RI value is at a low level, indicating that the resource scheduling effect is excellent, resources are reasonably used at the right time and the right place, and the resource utilization efficiency is high. Continue to implement the current scheduling strategy, maintain the stability and efficiency of the supply chain, and continue to optimize;

[0047] Medium scheduling level RIM ≤RI <RI L ; The RI value is at a medium level, indicating that the resource scheduling effect is average and there is room for improvement. We need to conduct in-depth analysis of each link in the scheduling process to find out the key factors and bottlenecks that affect the scheduling effect. We need to formulate specific improvement measures for the problems analyzed. After implementing the improvement measures, we need to pay close attention to the changes in the RI value and make necessary adjustments and optimizations based on the actual situation.

[0048] Poor scheduling level RI ≥ RI L ; The RI value is at a high level, indicating that the resource scheduling effect is poor, the resource utilization efficiency is low, and there is a large room for improvement. Immediately activate the emergency response mechanism and take emergency measures to alleviate the current resource shortage or surplus situation to ensure the continuity and stability of the supply chain. Conduct a comprehensive review of the scheduling strategy and resource allocation mechanism to find out the root cause of the problem and strengthen communication and collaboration among all links in the supply chain;

[0049] Among them, RI is the resource scheduling evaluation index, RI M is the lower threshold corresponding to the medium scheduling level and the upper threshold corresponding to the excellent scheduling level, RI L It is the lower threshold corresponding to the poor scheduling level and the upper threshold corresponding to the medium scheduling level.

[0050] Preferably, in the resource scheduling module, the process of implementing dynamic resource adjustment and optimal configuration includes:

[0051] Collect and integrate the current resource status, run the supply chain scheduling forecast model, analyze resource demand, sales trends and inventory changes, and calculate the current resource scheduling evaluation index to evaluate the current resource scheduling effect. If the value of the resource scheduling evaluation index is high, it means that the current scheduling effect is not ideal and needs to be adjusted; if the value of the resource scheduling evaluation index is low, it means that the scheduling effect is good, but it is also necessary to pay attention to whether there is room for further optimization;

[0052] Based on the forecast results and the analysis of resource scheduling evaluation index, formulate a specific resource scheduling plan, including determining the resource allocation amount, allocation time, allocation location and transportation method, and communicate the formulated resource scheduling plan to all participants in the supply chain;

[0053] Monitor and track the actual situation of resource flow, including the arrival time, quantity, quality, etc. of resources, and adjust the resource scheduling plan based on the monitoring results and new forecast data to cope with uncertainties and changes in the supply chain.

[0054] Preferably, in the monitoring and optimization module, the process of monitoring the overall supply chain management process includes:

[0055] Collect operational data from all links of the supply chain and track every key link in the supply chain in real time to identify and respond to potential problems and bottlenecks;

[0056] Collect user feedback, combine the supply chain scheduling prediction model and the evaluation results of the resource scheduling evaluation index, analyze the resource scheduling effect, identify the problems and bottlenecks in supply chain management, and conduct in-depth analysis of the identified problems to find out the root causes and influencing factors of the problems;

[0057] Based on the results of problem diagnosis, formulate corresponding response measures, such as adjusting production plans, optimizing inventory strategies, improving logistics processes, etc., to adjust and optimize the overall supply chain management strategy.

[0058] The present invention provides a supply chain multi-party sharing management system based on a digital trading platform. It has the following beneficial effects:

[0059] 1. This supply chain multi-party sharing management system based on a digital trading platform uses resource scheduling demand forecast results and combines current resource conditions to dynamically adjust resource allocation to ensure that resources are effectively utilized at the right time and place. The ability to dynamically adjust and optimize configuration significantly improves resource utilization efficiency and reduces resource waste. It can also quickly adapt to market changes and respond to emergency needs. The resource scheduling evaluation index provides a quantitative evaluation tool for resource scheduling, so as to intelligently allocate and optimize various resources in the supply chain.

[0060] 2. The supply chain multi-party shared management system based on the digital trading platform, through the application of supply chain scheduling prediction model and resource scheduling evaluation index, enables users to adjust resource scheduling measurement according to the evaluation results of the current resource scheduling effect, so as to achieve accurate resource allocation, reduce resource waste, improve resource utilization efficiency, and thus enhance the resilience and stability of the supply chain. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 This is a module structure diagram of a supply chain multi-party sharing management system based on a digital trading platform of the present invention;

[0062] Figure 2 A flow chart for evaluating resource scheduling effects of the present invention;

[0063] Figure 3 This is a flow chart for obtaining the resource scheduling evaluation index of the present invention. DETAILED DESCRIPTION

[0064] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are provided for the purpose of illustration and description, and are not intended to be exhaustive or to limit the present invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention, and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

[0065] The first embodiment, as Figures 1 to 3 As shown, the present invention provides a technical solution: a supply chain multi-party sharing management system based on a digital transaction platform, including a supply chain management platform, the supply chain management platform is communicatively connected with a data collection and integration module, a prediction and analysis module, a resource scheduling module, a collaborative operation module and a monitoring and optimization module, wherein the modules are connected by electrical signals;

[0066] The data collection and integration module is used to collect multi-source supply chain data from various supply chain participants, including inventory, production progress and sales data, and pre-process and integrate the collected multi-source supply chain data. The supply chain participants include suppliers, manufacturers and distributors. The data collection and integration module includes a data collection unit, a pre-processing unit and a data integration unit. The data collection unit is used to clarify the type of supply chain data to be collected and establish a data interface to collect supply chain data. The pre-processing unit is used to pre-process the collected data. The pre-processing process includes cleaning, sorting and standardization to ensure data quality and consistency. The data integration unit is used to integrate the pre-processed multi-source supply chain data, and prioritize the resources to be scheduled according to the importance of the supply chain resource scheduling process, obtain a resource scheduling sequence list, and form a global view of the supply chain, providing a basis for subsequent analysis and prediction.

[0067] Furthermore, the process of preprocessing and integrating the collected multi-source supply chain data includes:

[0068] Clearly define the types of supply chain data that need to be collected from each supply chain participant, namely inventory, production progress and sales data, and establish a unified data interface and transmission protocol to identify each supply chain participant, namely suppliers, manufacturers, and distributors, to ensure that data can be transmitted smoothly and securely. Inventory includes raw material inventory, work-in-progress inventory, finished product inventory, etc. Production progress includes production plan, actual production volume, production delays, etc. Sales data includes order volume, sales volume, sales revenue, return volume, etc. Use ETL tools to extract the required data from the data sources of each supply chain participant, collect multi-source supply chain data of each participant, and transfer the extracted data to the data warehouse. When extracting data, it is necessary to ensure the integrity and accuracy of the data to avoid omissions or errors. Among them, the data sources of each supply chain participant are ERP system, CRM system, and database. Preprocess the collected data to improve the quality and accuracy of the data by cleaning to remove duplicate data, process missing values, and correct erroneous data. , provide a reliable basis for subsequent analysis and prediction, and convert data from different sources and formats into a unified format and standard so that they can be easily processed in the subsequent data integration and analysis process, classify the pre-processed supply chain data according to the supply chain data type, associate data from different sources, and fuse the associated data, and fuse inventory data, production progress data, sales data, etc. together to fully understand the operation of the supply chain. Based on the integrated supply chain data, analyze the resource demand in the supply chain, and prioritize the resources to be scheduled according to the importance and urgency of the resource scheduling process, determine the resource scheduling sequence, generate a resource scheduling sequence table based on the results of the priority division, clarify the scheduling order and priority of each resource, and build a global view of the supply chain based on the integrated data and resource scheduling sequence table, showing each link, participant, resource flow, etc. of the supply chain, so as to fully understand the operation status and potential problems of the supply chain;

[0069] The forecasting analysis module is used to perform demand analysis on supply chain data, extract the forecasting features of the supply chain's production-demand ratio, production-sales ratio, sales growth rate, inventory turnover rate, and safety stock, traverse the relevant data of the forecasting features, obtain the supply chain forecasting feature table, and build a supply chain scheduling forecasting model based on machine learning technology to forecast and analyze the supply chain's resource demand, sales trend, and inventory changes, evaluate the resource scheduling effect, traverse the pre-processed inventory, production progress, and sales data collected from all participants in the supply chain, perform demand analysis, and extract the associated forecasting features of the supply chain forecast, which are the production-demand ratio, production-sales ratio, sales growth rate, inventory turnover rate, and safety stock. The production-demand ratio reflects the ratio of the number of products produced by the enterprise to the demand of its users for the product, and is an important indicator for measuring the degree of matching between production and sales. The production-sales ratio is similar to the production-demand ratio, but focuses more on the sales link, reflecting the market acceptance and sales efficiency of the enterprise's products. The sales growth rate represents the growth of sales volume, and is an important indicator for evaluating market potential and enterprise growth capabilities. The inventory turnover rate reflects the speed of inventory turnover and is a measure of inventory management efficiency. The key indicator of the rate is the safety stock, which is the stock set to ensure the stability of the supply chain, used to deal with sudden demand or supply interruption. Combined with various forecast features and pre-processed inventory, production progress and sales data, the forecast feature related data is integrated to obtain the supply chain forecast feature table, and the historical data of each forecast feature in the supply chain forecast feature table is divided to obtain the training set and the test set. The training set data is combined with machine learning technology to build a supply chain scheduling forecast model, and the test set data is used to test the supply chain scheduling forecast model. The supply chain scheduling forecast model is built based on the linear regression model. Combined with the resource scheduling sequence table, forecast feature data and the supply chain scheduling forecast model, the resource scheduling evaluation index is obtained. Different scheduling levels are set according to the resource scheduling evaluation index, which are excellent scheduling level, medium scheduling level and poor scheduling level, and corresponding evaluation thresholds are set for each scheduling level. Based on the resource scheduling evaluation index and the supply chain scheduling forecast model, the resource demand, sales trend and inventory changes of the supply chain are predicted and analyzed to determine the scheduling level and evaluate the pros and cons of the current resource scheduling effect.

[0070] Furthermore, the process of obtaining the resource scheduling evaluation index includes:

[0071] Calculate the resource demand satisfaction index based on the resource scheduling sequence table and the predicted resource demand, and preset the standard value Std of the resource demand satisfaction index D , calculate the adjustment value of resource demand satisfaction index, analyze the changing trend of resource demand, and the expression of resource demand satisfaction index is: D r is the resource demand satisfaction index, D is the actual resource demand, is the predicted resource demand output by the model, Da is the actual amount of resources allocated, D r The larger the value of, the higher the resource demand satisfaction;

[0072] Analyze the consistency between actual sales and predicted sales trends, calculate the sales trend matching index, and preset the standard value Std of the sales trend matching index S , calculate the sales trend matching index adjustment value, analyze the degree of sales trend matching index relative to the reference value, the expression of sales trend matching index is: S t is the sales trend matching index, S is the actual sales volume, is the predicted sales volume output by the model, S t The larger the value of, the higher the sales trend match;

[0073] Evaluate the management effect of inventory turnover rate and safety stock, calculate the inventory change control index, and preset the standard value Std of the inventory change control index I , calculate the inventory change control index adjustment value, analyze the inventory change control effect, the expression of the inventory change control index is: I c is the inventory change control index, ITO is the actual inventory turnover rate, and ITO t is the target inventory turnover rate, SI is the safety stock, SI op is the optimal safety stock, α and β are weight factors used to adjust the impact of inventory turnover rate and safety stock on the overall evaluation;

[0074] Combining the resource demand satisfaction index, sales trend matching index, inventory change control index and their corresponding adjustment values, the resource scheduling evaluation index is obtained through weighted calculation to analyze the scheduling effect.

[0075] The resource scheduling module is used to coordinate the resource flow of each link in the supply chain according to the forecast results and current resource status, ensure that resources are reasonably used at the right time and place, realize dynamic adjustment and optimal allocation of resources, and improve resource utilization efficiency;

[0076] The collaborative operation module is used to promote collaborative operations and information sharing among all parties involved in the supply chain. It provides online collaborative tools, supports real-time communication and collaboration among multiple parties, coordinates and resolves problems and conflicts encountered in collaborative operations, and improves the response speed and flexibility of the entire supply chain.

[0077] The monitoring and optimization module is used to monitor the overall process of supply chain management and continuously optimize and upgrade the system based on actual operating conditions and user feedback.

[0078] The second embodiment is based on the first embodiment. Figures 1 to 3As shown, the expression of resource demand satisfaction index adjustment value is:

[0079]

[0080] Among them, Ad D is the resource demand satisfaction index adjustment value, D r is the resource demand satisfaction index, Std D is the standard value of the resource demand satisfaction index, Ad D The value of is between 0 and 1, where 0 means completely unsatisfied and 1 means completely satisfied. When the resource scheduling strategy can accurately and timely meet all or most resource requirements, the value approaches 1. On the contrary, if the resource shortage or surplus leads to unsatisfied demand, the value will decrease. D The value indicates that the resource scheduling strategy performs well in meeting demand, which helps improve customer satisfaction and business operation efficiency;

[0081] The expression of the sales trend matching index adjustment value is:

[0082]

[0083] Among them, Ad S is the sales trend matching index adjustment value, S t is the sales trend matching index, Std S is the standard value of the sales trend matching index, Ad S The value is between 0 and 1, where 0 indicates a complete mismatch and 1 indicates a complete match. When the resource scheduling strategy can accurately predict and adapt to changes in sales trends, the value approaches 1. If there is a deviation between resource scheduling and actual sales trends, the value will decrease. 高 Ad The S value indicates that the resource scheduling strategy is highly flexible and forward-looking, which helps to reduce inventory backlogs and improve sales efficiency;

[0084] The expression of inventory change control index adjustment value is:

[0085]

[0086] Among them, Ad I is the inventory change control index adjustment value, I c is the inventory change control index, Std I is the standard value of the inventory change control index, Ad I The value of is between 0 and 1, where 0 indicates extremely poor inventory control and 1 indicates perfect inventory control. When the inventory level is kept within a reasonable range, neither too high nor too low, the value approaches 1. Too high inventory will increase storage costs, while too low inventory may lead to out-of-stock situations. Both of these situations will cause the value to decrease.I The value indicates that the resource scheduling strategy performs well in controlling inventory, which helps reduce operating costs and improve capital turnover;

[0087] Furthermore, the expression of resource scheduling evaluation index is:

[0088]

[0089] Among them, RI is the resource scheduling evaluation index, Ad D is the resource demand satisfaction index adjustment value, Std D is the standard value of the sales trend matching index, w D is the weight coefficient of resource demand satisfaction, Ad S is the inventory change control index adjustment value, Std S is the standard value of the sales trend matching index, w S is the weight coefficient of inventory change control, Ad I is the inventory change control index adjustment value, Std I is the standard value of the inventory change control index, w I is the weight coefficient of inventory change control. It should be noted that when all Ad D 、Ad S 、Ad I Close to its corresponding Std D 、Std S 、Std I , RI will approach a smaller value, indicating that the scheduling effect is close to the standard state. D 、Ad S 、Ad I Deviation from its corresponding Std D 、Std S 、Std I When , RI will increase. The greater the deviation, the higher the RI value, indicating that the scheduling effect deviates more from the standard value;

[0090] In addition, multiple scheduling levels correspond to multiple evaluation thresholds, wherein the evaluation threshold includes an upper threshold and a lower threshold;

[0091] Multiple scheduling levels and multiple evaluation thresholds satisfy the following relationship:

[0092] Excellent scheduling level 0<RI <RI M ; The RI value is at a low level, indicating that the resource scheduling effect is excellent, resources are reasonably used at the right time and the right place, and the resource utilization efficiency is high. Continue to implement the current scheduling strategy, maintain the stability and efficiency of the supply chain, and continue to optimize;

[0093] Medium scheduling level RIM ≤RI <RI L ; The RI value is at a medium level, indicating that the resource scheduling effect is average and there is room for improvement. We need to conduct in-depth analysis of each link in the scheduling process to find out the key factors and bottlenecks that affect the scheduling effect. We need to formulate specific improvement measures for the problems analyzed. After implementing the improvement measures, we need to pay close attention to the changes in the RI value and make necessary adjustments and optimizations based on the actual situation.

[0094] Poor scheduling level RI ≥ RI L ; The RI value is at a high level, indicating that the resource scheduling effect is poor, the resource utilization efficiency is low, and there is a large room for improvement. Immediately activate the emergency response mechanism and take emergency measures to alleviate the current resource shortage or surplus situation to ensure the continuity and stability of the supply chain. Conduct a comprehensive review of the scheduling strategy and resource allocation mechanism to find out the root cause of the problem and strengthen communication and collaboration among all links in the supply chain;

[0095] Among them, RI is the resource scheduling evaluation index, RI M is the lower threshold corresponding to the medium scheduling level and the upper threshold corresponding to the excellent scheduling level, RI L The lower threshold corresponding to the poor scheduling level and the upper threshold corresponding to the medium scheduling level;

[0096] In the resource scheduling module, the process of implementing dynamic resource adjustment and optimal configuration includes:

[0097] Collect and integrate current resource status, run supply chain scheduling forecasting models, analyze resource demand, sales trends and inventory changes, and calculate the current resource scheduling evaluation index to evaluate the current resource scheduling effect. If the value of the resource scheduling evaluation index is high, it means that the current scheduling effect is not ideal and needs to be adjusted; if the value of the resource scheduling evaluation index is low, it means that the scheduling effect is good, but it is also necessary to pay attention to whether there is room for further optimization. Based on the forecast results and the analysis of the resource scheduling evaluation index, formulate a specific resource scheduling plan, including determining the allocation amount, allocation time, allocation location and transportation method of resources, and communicate the formulated resource scheduling plan to all participants in the supply chain, monitor and track the actual situation of resource flow, including the arrival time, quantity, quality, etc. of resources, and adjust the resource scheduling plan based on the monitoring results and new forecast data to cope with uncertainties and changes in the supply chain;

[0098] In the monitoring and optimization module, the process of monitoring the overall supply chain management process includes:

[0099] Collect operation data of each link in the supply chain, and track each key link in the supply chain in real time, discover and respond to potential problems and bottlenecks, collect user feedback, combine the evaluation results of the supply chain scheduling prediction model and the resource scheduling evaluation index, analyze the resource scheduling effect, identify the problems and bottlenecks in supply chain management, and conduct in-depth analysis of the identified problems to find out the root causes and influencing factors of the problems. According to the results of problem diagnosis, formulate corresponding response measures, such as adjusting production plans, optimizing inventory strategies, improving logistics processes, etc., to adjust and optimize the overall supply chain management strategy.

[0100] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field and related fields without creative work should fall within the scope of protection of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention are implemented according to the conventional means in the field unless otherwise specified and limited.

Claims

1. A supply chain multi-party sharing management system based on a digital transaction platform, including a supply chain management platform, characterized in that: The supply chain management platform is communicatively connected with a data collection and integration module, a forecasting and analysis module, a resource scheduling module, a collaborative operation module, and a monitoring and optimization module, wherein electrical signals are connected between the modules; The data collection and integration module is used to collect multi-source supply chain data from various supply chain participants, including inventory, production progress and sales data, and pre-process and integrate the collected multi-source supply chain data, wherein the supply chain participants include suppliers, manufacturers and distributors; The forecasting and analysis module is used to perform demand analysis on supply chain data, extract forecasting features of the supply chain's production-demand ratio, production-sales ratio, sales growth rate, inventory turnover rate, and safety inventory, traverse relevant data of the forecasting features, obtain a supply chain forecasting feature table, and build a supply chain scheduling forecasting model based on machine learning technology, conduct forecasting and analysis on the supply chain's resource demand, sales trends, and inventory changes, and evaluate the resource scheduling effect; The resource scheduling module is used to coordinate the resource flow of each link in the supply chain according to the prediction results and the current resource status, so as to realize the dynamic adjustment and optimal allocation of resources; The collaborative operation module is used to promote collaborative operations and information sharing among supply chain participants; The monitoring and optimization module is used to monitor the overall process of supply chain management and continuously optimize and upgrade the system based on actual operating conditions and user feedback.

2. A supply chain multi-party sharing management system based on a digital trading platform according to claim 1, characterized in that: The data acquisition and integration module includes a data collection unit, a preprocessing unit and a data integration unit; The data collection unit is used to identify the types of supply chain data to be collected and to establish a data interface to collect supply chain data; The preprocessing unit is used to preprocess the collected data; The data integration unit is used to integrate the pre-processed multi-source supply chain data, and prioritize the resources to be scheduled according to the importance of the supply chain resource scheduling process to obtain a resource scheduling sequence table.

3. A supply chain multi-party sharing management system based on a digital trading platform according to claim 2, characterized in that: In the data collection and integration module, the process of preprocessing and integrating the collected multi-source supply chain data includes: Clarify the types of supply chain data that need to be collected from each supply chain participant, namely inventory, production progress, and sales data, and establish a unified data interface and transmission protocol to identify each supply chain participant, namely suppliers, manufacturers, and distributors; Use ETL tools to extract the required data from the data sources of each supply chain participant, collect the multi-source supply chain data of each participant, and transfer the extracted data to the data warehouse. The data sources of each supply chain participant are ERP system, CRM system, and database; Pre-process the collected data and convert data from different sources and formats into a unified format and standard; Classify the pre-processed supply chain data according to the supply chain data type, associate data from different sources, and fuse the associated data; Based on the integrated supply chain data, the resource demand in the supply chain is analyzed, and the resources to be scheduled are prioritized and the resource scheduling sequence is determined according to the importance and urgency of the resource scheduling process; Based on the results of the priority division, a resource scheduling sequence table is generated to clarify the scheduling order and priority of each resource, and a global view of the supply chain is constructed based on the integrated data and resource scheduling sequence table.

4. A supply chain multi-party sharing management system based on a digital trading platform according to claim 3, characterized in that: In the prediction and analysis module, the process of evaluating the resource scheduling effect includes: Traverse the pre-processed inventory, production progress and sales data collected from various supply chain participants, conduct demand analysis, and extract the associated prediction features of supply chain forecasting, which are production-demand ratio, production-sales ratio, sales growth rate, inventory turnover rate and safety stock; Combine each forecast feature with the pre-processed inventory, production schedule, and sales data to integrate the forecast feature related data and obtain the supply chain forecast feature table; The historical data of each prediction feature in the supply chain prediction feature table is divided into a training set and a test set. The training set data is combined with machine learning technology to build a supply chain scheduling prediction model, and the test set data is used to test the supply chain scheduling prediction model. The supply chain scheduling prediction model is built based on a linear regression model. Combining the resource scheduling sequence table, prediction feature data and supply chain scheduling prediction model, the resource scheduling evaluation index is obtained, and different scheduling levels are set according to the resource scheduling evaluation index, namely, excellent scheduling level, medium scheduling level and poor scheduling level, and corresponding evaluation thresholds are set for each scheduling level; Based on the resource scheduling evaluation index and supply chain scheduling forecasting model, the supply chain resource demand, sales trend and inventory changes are predicted and analyzed to determine the scheduling level and evaluate the quality of the current resource scheduling effect.

5. A supply chain multi-party sharing management system based on a digital trading platform according to claim 4, characterized in that: The process of obtaining the resource scheduling evaluation index includes: Calculate the resource demand satisfaction index based on the resource scheduling sequence table and the predicted resource demand, and preset the standard value Std of the resource demand satisfaction index D , calculate the resource demand satisfaction index adjustment value, analyze the change trend of resource demand, and the expression of the resource demand satisfaction index is: is the resource demand satisfaction index, D is the actual resource demand, is the predicted resource demand output by the model, D a is the actual amount of allocated resources, D r The larger the value of, the higher the resource demand satisfaction; Analyze the consistency between actual sales and predicted sales trends, calculate the sales trend matching index, and preset the standard value Std of the sales trend matching index S , calculate the sales trend matching index adjustment value, analyze the degree of sales trend matching index relative to the reference value, and the expression of the sales trend matching index is: S t is the sales trend matching index, S is the actual sales volume, is the predicted sales volume output by the model, S t The larger the value of, the higher the sales trend match; Evaluate the management effect of inventory turnover rate and safety stock, calculate the inventory change control index, and preset the standard value Std of the inventory change control index I , calculate the inventory change control index adjustment value, and analyze the inventory change control effect. The expression of the inventory change control index is: I c is the inventory change control index, ITO is the actual inventory turnover rate, and ITO t is the target inventory turnover rate, S I is the safety stock, SI op is the optimal safety stock, α and β are weight factors used to adjust the impact of inventory turnover rate and safety stock on the overall evaluation; Combining the resource demand satisfaction index, sales trend matching index, inventory change control index and their corresponding adjustment values, a weighted calculation is performed to obtain the resource scheduling evaluation index, and the scheduling effect is analyzed.

6. A supply chain multi-party sharing management system based on a digital trading platform according to claim 5, characterized in that: The resource demand meets the index adjustment value expression as follows: Among them, Ad D is the resource demand satisfaction index adjustment value, D r is the resource demand satisfaction index, Std D is the standard value of resource demand satisfaction index, Ad D The value of is between 0 and 1, 0 means completely unsatisfied and 1 means completely satisfied; The expression of the sales trend matching index adjustment value is: Among them, Ad S is the sales trend matching index adjustment value, S t is the sales trend matching index, Std S is the standard value of the sales trend matching index, Ad S The value is between 0 and 1, 0 means no match at all, 1 means a perfect match; The expression of the inventory change control index adjustment value is: Among them, Ad I is the inventory change control index adjustment value, I c is the inventory change control index, Std I is the standard value of the inventory change control index, Ad I The value of is between 0 and 1, where 0 indicates extremely poor inventory control and 1 indicates perfect inventory control.

7. A supply chain multi-party sharing management system based on a digital trading platform according to claim 6, characterized in that: The expression of the resource scheduling evaluation index is: Among them, RI is the resource scheduling evaluation index, Ad D is the resource demand satisfaction index adjustment value, Std D is the standard value of the sales trend matching index, w D is the weight coefficient of resource demand satisfaction, Ad S is the inventory change control index adjustment value, Std S is the standard value of the sales trend matching index, w S is the weight coefficient of inventory change control, Ad I is the inventory change control index adjustment value, Std I is the standard value of the inventory change control index, w I It is the weight coefficient for inventory change control. It should be noted that the higher the RI value, the greater the deviation between the scheduling effect and the standard value.

8. A supply chain multi-party sharing management system based on a digital trading platform according to claim 7, characterized in that: A plurality of the scheduling levels correspond to a plurality of the evaluation thresholds, wherein the evaluation thresholds include an upper threshold and a lower threshold; The multiple scheduling levels and the multiple evaluation thresholds satisfy the following relationship: Excellent scheduling level 0<RI<RI M ; Medium scheduling level RI M ≤RI<RI L ; Poor scheduling level RI ≥ RI L ; Among them, RI is the resource scheduling evaluation index, RI M is the lower threshold corresponding to the medium scheduling level and the upper threshold corresponding to the excellent scheduling level, RI L It is the lower threshold corresponding to the poor scheduling level and the upper threshold corresponding to the medium scheduling level.

9. A supply chain multi-party sharing management system based on a digital trading platform according to claim 8, characterized in that: In the resource scheduling module, the process of implementing dynamic resource adjustment and optimal configuration includes: Collect and integrate current resource status, run supply chain scheduling forecasting models, analyze resource demand, sales trends, and inventory changes, and calculate the current resource scheduling evaluation index to evaluate the current resource scheduling effect; Based on the analysis of forecast results and resource scheduling evaluation index, formulate a specific resource scheduling plan and communicate the formulated resource scheduling plan to all participants in the supply chain; Monitor and track the actual situation of resource flow, and adjust resource scheduling plans based on monitoring results and new forecast data to cope with uncertainties and changes in the supply chain.

10. A supply chain multi-party sharing management system based on a digital trading platform according to claim 9, characterized in that: In the monitoring and optimization module, the process of monitoring the overall supply chain management process includes: Collect operational data from all links of the supply chain and track every key link in the supply chain in real time to identify and respond to potential problems and bottlenecks; Collect user feedback, combine the supply chain scheduling prediction model and the evaluation results of the resource scheduling evaluation index, analyze the resource scheduling effect, identify the problems and bottlenecks in supply chain management, and conduct in-depth analysis of the identified problems to find out the root causes and influencing factors of the problems; Based on the results of problem diagnosis, formulate corresponding response measures and adjust and optimize the overall supply chain management strategy.

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