A collaborative fuel interaction management system

Abstract

The present invention provides a collaborative fuel interaction management system, which belongs to the technical field of supply chain management. The system includes a relevant determination module, a risk point module, an inefficiency point module and a strategy module. By integrating and analyzing data from different departments, the inefficiency points and risk points in the internal and external supply chains are determined, and strategies are formulated based on this priority. The modules in the system cooperate with each other, monitor the supply chain status in real time, conduct risk assessment and efficiency analysis, formulate specific targeted measures, improve the transparency, efficiency and risk management capabilities of the supply chain, reduce operating costs, improve the response speed and flexibility of the supply chain, strengthen the decision support system, and ensure the stability and sustainability of the fuel supply chain.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain management, and in particular to a collaborative fuel interaction management system. Background Art

[0002] In the field of fuel interaction management, key issues include how to effectively monitor and optimize the entire process of fuel from suppliers to end users, including fuel procurement, storage, transportation and distribution. With the intensification of globalization and market competition, higher requirements are placed on the management of the fuel supply chain, and more complex logistics, inventory, and distribution issues need to be solved. In the existing technology, the various links in the supply chain may lack integration, resulting in waste of resources and insufficient synergy.

[0003] Therefore, the present invention provides a coordinated fuel interaction management system. Summary of the invention

[0004] The present invention provides a collaborative fuel interaction management system, which integrates and analyzes data from different departments, identifies inefficiencies and risk points in internal and external supply chains, and formulates strategies based on this priority. The modules in the system collaborate with each other to monitor the supply chain status in real time, conduct risk assessment and efficiency analysis, and formulate specific targeted measures to improve supply chain transparency, efficiency and risk management capabilities, reduce operating costs, improve supply chain response speed and flexibility, strengthen decision support systems, and ensure the stability and sustainability of the fuel supply chain.

[0005] The present invention provides a coordinated fuel interaction management system, comprising:

[0006] Correlation determination module: performs correlation analysis on the data sources and integration platforms covered by data from different departments, identifies and maps the correlation between data from different departments based on the analysis results, and integrates departmental data from different departments based on the correlation;

[0007] Risk point module: evaluate the internal supply chain status, determine the performance status of the internal supply chain, and derive possible internal supply chain risk points based on the performance status;

[0008] Inefficiency point module: Identify the links in the external supply chain and determine the inefficiency points in the external supply chain based on the identification results;

[0009] Strategy module: Prioritize the risk points and inefficiency points according to the relevant connections, formulate corresponding specific strategies according to the ranking results, and then realize the management of fuel interaction.

[0010] The present invention provides a coordinated fuel interaction management system, characterized in that the relevant determination module includes:

[0011] Target determination unit: evaluate the data needs of each department, clarify the types and sources of integrated data, and determine the goals and expected results of data integration;

[0012] Data evaluation unit: Determine the data differences between departments and the integration platform, and perform correlation analysis on department data elements and integration platform data elements. Combine the analysis results with the data differences to determine whether data elements need to be converted, and establish corresponding mapping rules for elements that need to be converted.

[0013] Review unit: Review data sources, identify the types of conflicts that may occur during data integration, analyze the root causes of the conflicts, and develop corresponding solutions based on the root causes;

[0014] Integration unit: collects corresponding department data according to the solution, converts the department data into platform data corresponding to the integration platform based on mapping rules and related connections, divides the platform data according to department names, and determines internal supply chain or external supply chain.

[0015] The present invention provides a coordinated fuel interaction management system, a risk point module, including:

[0016] Process unit: collects node information of the internal supply chain, determines the supply chain process based on the node information, and obtains relevant operation details and historical performance data;

[0017] Key Node Unit: Determine the business objectives that need to be supported by internal supply chain management, conduct a key assessment of the current status of the internal supply chain in combination with business objectives, relevant operational details and historical performance data, and identify key nodes in the internal supply chain;

[0018] Performance evaluation unit: evaluates the efficiency of the internal supply chain operation according to the key nodes, identifies the performance status of the internal supply chain, and uses pre-set key performance evaluation indicators to diagnose the overall and local performance of the internal supply chain;

[0019] Risk point determination unit: Based on the diagnosis results, the internal supply chain risk points are determined.

[0020] The present invention provides a coordinated fuel interaction management system and a performance evaluation unit, comprising:

[0021] Performance determination block: Determine the key performance indicators that need to be tracked and evaluated at each key node based on the internal supply chain, collect the actual operation data of each key node, and determine the actual performance of the corresponding key node;

[0022] Efficiency block: compares the actual performance of each key node with the fuel industry standard to derive the operating efficiency of the internal supply chain;

[0023] Area block: Determine the scope and dimension of identification according to the key nodes, determine the performance status of the internal supply chain based on the scope and dimension combined with the comparison results of the efficiency block, and obtain the strong and weak areas;

[0024] Diagnostic block: The operational efficiency, strong and weak areas and pre-set key performance evaluation indicators are used to conduct root cause analysis on inefficient points and weak areas of operational efficiency, determine the specific causes of poor performance, and diagnose the overall and local performance of the internal supply chain based on the specific causes.

[0025] The present invention provides a coordinated fuel interaction management system, a low efficiency module, comprising:

[0026] Starting point unit: List all suppliers of fuel-related products and related downstream products, and determine the starting point of the external supply chain, where the suppliers include direct suppliers and indirect suppliers;

[0027] Supply Chain Determination Unit: Evaluate the carriers of fuel transportation and the distributors responsible for regional fuel allocation, determine the process lines and intermediate points of the external supply chain, determine the end point of the external supply chain according to the end users, and then determine the external supply chain;

[0028] Risk level unit: formulate external supply chain risk assessment standards from two dimensions: the possibility of risk occurrence and the degree of impact caused by the risk, conduct risk assessment on the external supply chain, determine the risks that may affect each link of the external supply chain, and determine the internal and external environmental causes corresponding to each risk, and then determine the risk level of each link;

[0029] Performance indicator unit: According to the operational data of each link in the external supply chain, determine the characteristics of the corresponding link, and determine the key performance indicators of the corresponding link based on the characteristics of the link and the risk level;

[0030] Inefficiency low point unit: compare the operational data of each link with the corresponding key performance indicators to determine the inefficiency points.

[0031] The present invention provides a coordinated fuel interaction management system, a risk level unit, comprising:

[0032] Calculation block: Determine the risk level of the corresponding link based on the operational data of each link and combining internal and external environmental factors;

[0033] ;

[0034] in, Indicates the risk level; , , and They represent the possible level weight coefficient, the impact level weight coefficient, the recovery difficulty level weight coefficient and the detection difficulty level weight coefficient respectively; Indicates the possible level, express The number of inefficiencies that occurred during the time period; Indicates the level of impact; express The extent of the negative impact of inefficiencies during the time period; Indicates the level of difficulty in recovery; It indicates the time it takes for the supply chain to return to normal after an inefficiency occurs; represents the recovery cost; Indicates the level of detection difficulty; Indicates the monitoring effectiveness of the corresponding low efficiency point; Indicates transparency of monitoring data; It represents the adjustment function of the influence factor of the external environment impact adjustment data x and the internal environment impact adjustment data y on the low efficiency point.

[0035] The present invention provides a coordinated fuel interaction management system, a strategy module, including:

[0036] Probability unit: Calculate the probability of the corresponding point occurring based on the relevant data of each risk point and inefficiency point;

[0037] Matrix unit: Evaluate the specific impact of each risk point and inefficiency point, establish a risk matrix, and map each risk point and inefficiency point onto the risk matrix based on the results of probability calculation and impact analysis;

[0038] Priority unit: Assign a quantitative score to each risk point and inefficiency point, and determine the priority of each risk point and inefficiency point;

[0039] Improvement Unit: Develop improvement measures for each high-risk point and low-efficiency point based on priority.

[0040] The present invention provides a coordinated fuel interaction management system, a matrix unit, and further includes:

[0041] According to the probability of occurrence of risk points and inefficiency points as the X-axis and the influencing factors as the Y-axis, the positions of the corresponding risk points and inefficiency points in the risk matrix are located.

[0042] Compared with the existing technology, the beneficial effects of this application are as follows: by integrating and analyzing data from different departments, the inefficiencies and risk points in the internal and external supply chains are identified, and strategies are formulated based on this priority. The modules in the system collaborate with each other to monitor the supply chain status in real time, conduct risk assessment and efficiency analysis, and formulate specific targeted measures to improve supply chain transparency, efficiency and risk management capabilities, reduce operating costs, improve supply chain response speed and flexibility, strengthen decision-making support systems, and ensure the stability and sustainability of the fuel supply chain.

[0043] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0044] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0046] Figure 1 It is a structural diagram of a collaborative fuel interaction management system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0048] Embodiment 1:

[0049] The embodiment of the present invention provides a coordinated fuel interaction management system, such as Figure 1 As shown, including:

[0050] Correlation determination module: performs correlation analysis on the data sources and integration platforms covered by data from different departments, identifies and maps the correlation between data from different departments based on the analysis results, and integrates departmental data from different departments based on the correlation;

[0051] Risk point module: evaluate the internal supply chain status, determine the performance status of the internal supply chain, and derive possible internal supply chain risk points based on the performance status;

[0052] Inefficiency point module: Identify the links in the external supply chain and determine the inefficiency points in the external supply chain based on the identification results;

[0053] Strategy module: Prioritize the risk points and inefficiency points according to the relevant connections, formulate corresponding specific strategies according to the ranking results, and then realize the management of fuel interaction.

[0054] In this embodiment, correlation analysis is the process of determining the relationship between different data elements, including identifying the meaning and purpose of each data element; analyzing the functions of data elements in different departments or systems; evaluating the logical relationship between different data elements; and identifying the commonalities and differences in data.

[0055] In this embodiment, the integration process achieves data consistency and information sharing through determination, review, evaluation and integration units, and performs data conversion by evaluating data requirements and differences and combining mapping rules to ensure that data is correctly integrated between different departments.

[0056] In this embodiment, the performance status relates to the following aspects: current operation efficiency, cost control status, effectiveness of inventory management, and the ability to cope with demand fluctuations.

[0057] In this embodiment, the risk point determination process establishes the supply chain process by collecting node information diagrams, and obtains specific operations and historical performance data therefrom, evaluates business goals and performance data to identify key nodes in the supply chain, uses key performance indicators to evaluate and diagnose supply chain efficiency, and finally analyzes these data to determine potential risk points.

[0058] In this embodiment, the relevant connection is the correlation between the data sources of different departments, specifically refers to the logical connection, interdependent relationship or functional connection point between the data. The relevant connection includes data overlap points: for example, both departments use customer ID to identify customer information; the consistency of data application scenarios: the data output by one department may be the data input by another department; the logical order of data in the organizational process: for example, sales data may affect inventory management; the causal relationship between data: such as marketing activities (marketing department) may affect sales (sales department).

[0059] In this embodiment, the inefficiency point refers to the link in the supply chain that performs poorly relative to the key performance indicators.

[0060] In this embodiment, the priority determination process is to sort all risk points and inefficiency points according to the results of quantitative scoring, and points with higher values ​​will be given higher priorities, which means that they will receive earlier attention and resource allocation.

[0061] In this embodiment, the process of determining improvement measures is to calculate the probability of occurrence of risk points and inefficiency points in the internal supply chain, evaluate the specific impact of each risk and inefficiency point, and establish a risk matrix. The points are mapped to the matrix according to probability and impact, and the points are quantitatively scored to determine the order of priority treatment, and specific improvement measures are formulated for the points with high scores.

[0062] The working principle and beneficial effects of the above technical solution are: by integrating and analyzing data from different departments, the inefficiencies and risk points in the internal and external supply chains are identified, and strategies are formulated based on this priority. The modules in the system collaborate with each other to monitor the supply chain status in real time, conduct risk assessment and efficiency analysis, and formulate specific targeted measures to improve supply chain transparency, efficiency and risk management capabilities, reduce operating costs, improve supply chain response speed and flexibility, strengthen decision-making support systems, and ensure the stability and sustainability of the fuel supply chain.

[0063] Embodiment 2:

[0064] The embodiment of the present invention provides a coordinated fuel interaction management system, and the related determination module includes:

[0065] Target determination unit: evaluate the data needs of each department, clarify the types and sources of integrated data, and determine the goals and expected results of data integration;

[0066] Data evaluation unit: Determine the data differences between departments and the integration platform, and perform correlation analysis on department data elements and integration platform data elements. Combine the analysis results with the data differences to determine whether data elements need to be converted, and establish corresponding mapping rules for elements that need to be converted.

[0067] Review unit: Review data sources, identify the types of conflicts that may occur during data integration, analyze the root causes of the conflicts, and develop corresponding solutions based on the root causes;

[0068] Integration unit: collects corresponding department data according to the solution, converts the department data into platform data corresponding to the integration platform based on mapping rules and related connections, divides the platform data according to department names, and determines internal supply chain or external supply chain.

[0069] In this embodiment, data requirements are the types and details of data required by various departments to perform their business operations and make decisions, including: sales data, customer feedback, inventory levels, supplier performance, fuel material costs, and transportation and logistics information.

[0070] In this embodiment, the goals and expected results are the end goals that are expected to be achieved through data integration, including improved data consistency and accuracy, seamless connection between data sources of different departments, data-driven decision support, improved operational efficiency, cost savings, and reduced time consumption.

[0071] In this embodiment, data differences refer to differences in data formats, standards, and quality among different departments or systems, which may involve different data formats (such as CSV, Excel, and SQL databases), different data granularities (such as detailed transaction data and monthly summary data), and differences in data standards (different departments use different naming conventions).

[0072] In this embodiment, the mapping rules are standards for converting data elements from different data sources into formats and structures recognized by the integration platform, including conversion rules for date and time formats, unit conversion for numerical data, and field name mapping (for example, "customer number" is converted to "CustID").

[0073] In this embodiment, the review process involves an in-depth analysis of the data sources to determine possible problems in data integration, such as redundant data, inconsistent data items, data quality issues, and permission and security issues.

[0074] In this embodiment, the solution is a countermeasure developed for the problems found during the review process, including data cleaning and deduplication strategies, data quality control measures, and access control and security protocols.

[0075] In this embodiment, the specific steps of dividing data and determining the supply chain are to divide the platform data according to the department name, and the step of determining the internal or external supply chain is to match the data on the integrated platform with a specific department or business process; identify whether the data belongs to the internal supply chain or the external supply chain according to the source department or the business scope of data use; establish access and use rules for data of the internal supply chain (such as processes within production, inventory, and distribution) or the external supply chain (such as suppliers, partners, and customer relationships); and clear possible topics and cross-departmental data integration points, such as establishing a link between inventory management and procurement, to ensure real-time updating and accuracy of data flows.

[0076] The working principle and beneficial effects of the above technical solution are: to achieve data consistency and information sharing through determination, review, evaluation and integration units, to convert data by evaluating data needs and differences and combining mapping rules to ensure the correct integration of data between different departments, and ultimately to achieve clear identification of internal and external supply chain risk points and inefficiencies and efficient strategy formulation, which will help improve the transparency and collaborative work efficiency of the supply chain, reduce operational risks, and enhance the overall supply chain operational efficiency and responsiveness.

[0077] Embodiment 3:

[0078] The embodiment of the present invention provides a coordinated fuel interaction management system, a risk point module, including:

[0079] Process unit: collects node information of the internal supply chain, determines the supply chain process based on the node information, and obtains relevant operation details and historical performance data;

[0080] Key Node Unit: Determine the business objectives that need to be supported by internal supply chain management, conduct a key assessment of the current status of the internal supply chain in combination with business objectives, relevant operational details and historical performance data, and identify key nodes in the internal supply chain;

[0081] Performance evaluation unit: evaluates the efficiency of the internal supply chain operation according to the key nodes, identifies the performance status of the internal supply chain, and uses pre-set key performance evaluation indicators to diagnose the overall and local performance of the internal supply chain;

[0082] Risk point determination unit: Based on the diagnosis results, the internal supply chain risk points are determined.

[0083] In this embodiment, node information refers to all important points in the supply chain, such as detailed information of suppliers of raw materials, production plants, warehouses, distribution centers, retailers, etc. Specifically, it includes: the location of the node, the inventory level of each node, production capacity, transportation time, cost and method, demand and supply under normal circumstances, contact between nodes (such as purchase orders, logistics information, etc.), and time information of node operations.

[0084] In this embodiment, the supply chain process is to analyze node information to understand the flow path and conversion process of materials and products, which usually involves mapping the flow path of materials from suppliers to consumers, understanding the specific role of each node in the supply chain, and determining the key activities and decision points related to each node.

[0085] In this embodiment, the relevant operational details generally refer to the specific activities carried out at each node of the supply chain and how these activities operate; historical performance data includes past order completion status, historical inventory levels, time efficiency of transportation and production, cost data, and service levels (such as on-time delivery rate).

[0086] In this embodiment, the business objectives that supply chain management needs to support include cost reduction, service level improvement, inventory optimization, improvement of supply chain agility and flexibility, risk management, and sustainable development goals.

[0087] In this embodiment, the key evaluation contents include the efficiency and effect of each node, whether the material flow and information flow are smooth, whether there are bottlenecks or redundant processes, the coordination and cooperation between the nodes, and whether the transportation and production methods can be optimized.

[0088] In this embodiment, the key performance evaluation indicators include order on-time rate, inventory turnover rate, supply chain cost, inventory accuracy, supply chain flexibility index, customer satisfaction and supply chain carbon footprint, etc.

[0089] In this embodiment, the diagnostic process is to collect and organize all the data and information mentioned above; use data analysis and statistical methods to evaluate the efficiency of the internal supply chain; check each link of the supply chain process and evaluate the performance of each node; compare with established goals and industry best practices; identify problem areas that deviate from goals and standards; identify possible risk points and improvement potential through comparative analysis; and propose optimization plans and improvement measures based on the analysis results.

[0090] The working principle and beneficial effects of the above technical solution are: establish the supply chain process by collecting node information diagrams, and obtain specific operation and historical performance data from them, evaluate business goals and performance data to identify key nodes in the supply chain, and use key performance indicators to evaluate and diagnose supply chain efficiency. Finally, analyze these data to determine potential risk points, improve the transparency of supply chain management, and strengthen the support role of key nodes for business success. By diagnosing supply chain performance, bottlenecks and risks can be discovered in advance, thereby optimizing operational processes and improving overall supply chain efficiency.

[0091] Embodiment 4:

[0092] The embodiment of the present invention provides a coordinated fuel interaction management system, a performance evaluation unit, including:

[0093] Performance determination block: Determine the key performance indicators that need to be tracked and evaluated at each key node based on the internal supply chain, collect the actual operation data of each key node, and determine the actual performance of the corresponding key node;

[0094] Efficiency block: compares the actual performance of each key node with the fuel industry standard to derive the operating efficiency of the internal supply chain;

[0095] Area block: Determine the scope and dimension of identification according to the key nodes, determine the performance status of the internal supply chain based on the scope and dimension combined with the comparison results of the efficiency block, and obtain the strong and weak areas;

[0096] Diagnostic block: The operational efficiency, strong and weak areas and pre-set key performance evaluation indicators are used to conduct root cause analysis on inefficient points and weak areas of operational efficiency, determine the specific causes of poor performance, and diagnose the overall and local performance of the internal supply chain based on the specific causes.

[0097] In this embodiment, actual operational data refers to data collected during the actual operation of each key node in the supply chain, including production data: production rate, batch size, downtime; logistics data: transportation time, delivery cycle, inventory turnover rate; quality data: qualification rate, return rate, customer complaints.

[0098] In this embodiment, actual performance refers to the performance of key nodes in actual operations, compared with set performance goals or standards, including production efficiency, order fulfillment speed, inventory management efficiency, and cost control level.

[0099] In this embodiment, operational efficiency refers to the efficiency level of supply chain operations, which generally involves the degree of resource utilization and the degree of time optimization, including resource utilization rate, operation cycle time, and overall time responsiveness of the supply chain.

[0100] In this embodiment, strong areas refer to those parts of the supply chain that perform well, are efficient, or exceed standards; weak areas refer to those parts that perform poorly, are inefficient, or do not meet standards, relative to industry standards or expected goals.

[0101] In this example, root cause analysis is a method used to identify the underlying causes of a problem, including data analysis to find trends and patterns (such as failure mode and effect analysis); process reviews to identify improper operations or process defects; discussions and interviews to understand practitioners' views and experiences; and the use of methods such as the "5 Whys" to deeply investigate the causes.

[0102] In this embodiment, the diagnosis process includes analyzing which links lead to insufficient performance, whether the insufficient performance is a temporary or persistent problem, and what impact the areas and links with insufficient performance have on the entire supply chain.

[0103] In this example, determining the specific causes of poor performance includes examining relevant operations and processes to ensure they are working as expected, checking whether external factors such as market changes or supply issues are affecting performance, examining whether employee training and support are sufficient, and analyzing whether technology, tools, and equipment are properly maintained and updated.

[0104] The working principle and beneficial effects of the above technical solution are: by tracking and evaluating the performance of key nodes in the internal supply chain, then comparing these performance data with industry standards to evaluate operational efficiency, analyzing these data to distinguish between strong and weak areas, and finally conducting root cause analysis of inefficient points and weak areas, diagnosing the performance status of internal and external supply chains, improving the accuracy and timeliness of supply chain problem diagnosis, optimizing supply chain management, and improving overall operational efficiency.

[0105] Embodiment 5:

[0106] The embodiment of the present invention provides a coordinated fuel interaction management system, a low efficiency module, including:

[0107] Starting point unit: List all suppliers of fuel-related products and related downstream products, and determine the starting point of the external supply chain, where the suppliers include direct suppliers and indirect suppliers;

[0108] Supply Chain Determination Unit: Evaluate the carriers of fuel transportation and the distributors responsible for regional fuel allocation, determine the process lines and intermediate points of the external supply chain, determine the end point of the external supply chain according to the end users, and then determine the external supply chain;

[0109] Risk level unit: formulate external supply chain risk assessment standards from two dimensions: the possibility of risk occurrence and the degree of impact caused by the risk, conduct risk assessment on the external supply chain, determine the risks that may affect each link of the external supply chain, and determine the internal and external environmental causes corresponding to each risk, and then determine the risk level of each link;

[0110] Performance indicator unit: According to the operational data of each link in the external supply chain, determine the characteristics of the corresponding link, and determine the key performance indicators of the corresponding link based on the characteristics of the link and the risk level;

[0111] Inefficiency low point unit: compare the operational data of each link with the corresponding key performance indicators to determine the inefficiency points.

[0112] In this embodiment, direct supply refers to manufacturers or companies that directly supply raw materials, components or products; indirect suppliers refer to manufacturers that provide auxiliary products or services in the supply chain and indirectly affect the supply chain through direct suppliers or other intermediaries.

[0113] In this embodiment, the distributor assessment process is an assessment performed on the distributor responsible for regional fuel allocation, including supply capacity and stability, delivery reliability, operational efficiency, and the ability to respond to temporary situations.

[0114] In this embodiment, the evaluation criteria are the criteria used when conducting risk assessment, including the probability of risk occurrence (e.g., high, medium, low), the severity of the impact caused by the risk (e.g., not serious, medium, serious). If the supplier stability of a link is poor and any supply interruption will cause the entire production to stagnate, the possibility and impact of the risk are very high, so the risk level of this link is likely to be assessed as high.

[0115] In this embodiment, operational data refers to data collected during supply chain operations, such as delivery time, arrival time, order accuracy, and inventory levels.

[0116] In this embodiment, link characteristics refer to the main characteristics and functions of each link, including the position of the link in the supply chain, the specific activities the link is responsible for, the input and output of the link, and the key resources and processes of the link.

[0117] In this embodiment, the key performance indicators are standards used to evaluate the performance of specific links, including on-time delivery ratio, transportation loss rate, inventory turnover rate and cost control.

[0118] In this embodiment, the process of indicator comparison is to collect operational data of each link; apply corresponding key performance indicators to the data of each link; analyze the gap between the actual performance of each link and the target or industry standard; identify the links with substandard performance, that is, the low efficiency points, and conduct in-depth analysis of the reasons for the gap.

[0119] The working principle and beneficial effects of the above technical solution are: by clarifying the source of the supply chain, using the supply chain to determine the unit structure of the entire link and identify important links, assessing the possible risks and levels of each link through risk assessment standards, and at the same time, determining key performance indicators based on operational data, comparing operational data with performance indicators, analyzing inefficient links, and effectively improving the accuracy and transparency of external supply chain management, assisting managers in optimizing the supply chain structure, and improving the stability and efficiency of the overall supply chain by identifying inefficiencies and risk levels.

[0120] Embodiment 6:

[0121] The embodiment of the present invention provides a coordinated fuel interaction management system, a risk level unit, including:

[0122] Calculation block: Determine the risk level of the corresponding link based on the operational data of each link and combining internal and external environmental factors;

[0123] ;

[0124] in, Indicates the risk level; , , and They represent the possible level weight coefficient, the impact level weight coefficient, the recovery difficulty level weight coefficient and the detection difficulty level weight coefficient respectively; Indicates the possible level, express The number of inefficiencies that occurred during the time period; Indicates the level of impact; express The extent of the negative impact of inefficiencies during the time period; Indicates the level of difficulty in recovery; It indicates the time it takes for the supply chain to return to normal after an inefficiency occurs; represents the recovery cost; Indicates the level of detection difficulty; Indicates the monitoring effectiveness of the corresponding low efficiency point; Indicates transparency of monitoring data; It represents the adjustment function of the influence factor of the external environment impact adjustment data x and the internal environment impact adjustment data y on the low efficiency point.

[0125] In this embodiment, the likelihood level is usually based on historical data and expert evaluation to quantify the likelihood of a risk occurring; the impact level assesses the extent of the negative impact on the supply chain when a risk event occurs; the recovery difficulty level assesses the difficulty required for the supply chain to return to normal operation after a risk event occurs; the detection difficulty level reflects how easy it is for a company to identify a risk event before it occurs, and the level can be assessed based on existing monitoring systems, data transparency, and early warning mechanisms.

[0126] The working principle and beneficial effects of the above technical solution are: by calculating the risk level, it assists managers in optimizing the supply chain structure, and by identifying inefficiencies and risk levels, it improves the stability and efficiency of the overall supply chain.

[0127] Embodiment 7:

[0128] The embodiment of the present invention provides a coordinated fuel interaction management system, a policy module, including:

[0129] In this embodiment, the specific impacts include the direct or indirect impact of risk points or inefficiencies on supply chain operations, such as production stagnation, cost increase, delivery delays, decreased customer satisfaction, etc.

[0130] In this embodiment, the mapping process is to place risk points and inefficiency points at corresponding positions in the risk matrix according to their probability and impact. The matrix uses probability and impact as two axes to judge the urgency and importance of each point.

[0131] In this embodiment, the quantitative scoring process scores the data of each risk point and inefficiency point according to established standards and methods (which may be algorithms or scoring models) to obtain a numerical result, which reflects the urgency of handling each point.

[0132] In this embodiment, the priority determination process is to sort all risk points and inefficiency points according to the results of quantitative scoring, and points with higher values ​​will be given higher priorities, which means that they will receive earlier attention and resource allocation.

[0133] In this embodiment, the risk matrix is ​​a tool used to identify and prioritize risks, and is usually composed of two dimensions: one is the probability of the risk occurring, and the other is the impact that the risk will cause if it occurs.

[0134] In this embodiment, the improvement measures are a series of actions and strategies taken for higher-ranked risk points and inefficiency points, including optimizing supply chain processes, increasing safety stocks, training employees, improving technical systems, establishing emergency plans, etc., aimed at reducing risks and improving efficiency.

[0135] The working principle and beneficial effects of the above technical solution are: by calculating the probability of occurrence of risk points and inefficiency points in the internal supply chain, evaluating the specific impact of each risk and inefficiency point, and establishing a risk matrix, mapping the points to the matrix according to probability and impact, and quantitatively scoring the points to determine the order of priority treatment, and formulating specific improvement measures for points with high scores, which helps to prioritize the identification and improvement of high-risk and inefficient links in the supply chain, thereby improving overall management efficiency and responsiveness.

[0136] Embodiment 8:

[0137] The embodiment of the present invention provides a coordinated fuel interaction management system, a matrix unit, and further includes:

[0138] According to the probability of occurrence of risk points and inefficiency points as the X-axis and the influencing factors as the Y-axis, the positions of the corresponding risk points and inefficiency points in the risk matrix are located.

[0139] The working principle and beneficial effects of the above technical solution are: by calculating the probability of occurrence of each risk point and inefficiency point, establishing a risk matrix to evaluate its impact, assigning weights to each point to determine the priority, and formulating improvement measures for high-risk and inefficiency points, it helps to reduce potential losses and achieve more robust supply chain operations.

[0140] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A collaborative fuel interaction management system, characterized in that: include: Correlation determination module: performs correlation analysis on the data sources and integration platforms covered by data from different departments, identifies and maps the correlation between data from different departments based on the analysis results, and integrates departmental data from different departments based on the correlation; Risk point module: evaluate the internal supply chain status, determine the performance status of the internal supply chain, and derive possible internal supply chain risk points based on the performance status; Inefficiency point module: Identify the links in the external supply chain and determine the inefficiency points in the external supply chain based on the identification results; Strategy module: prioritize the risk points and inefficiency points according to the relevant connections, formulate corresponding specific strategies according to the ranking results, and then realize the management of fuel interaction; Wherein, the relevant determination module includes: Target determination unit: evaluate the data needs of each department, clarify the types and sources of integrated data, and determine the goals and expected results of data integration; Data evaluation unit: Determine the data differences between departments and the integration platform, and perform correlation analysis on department data elements and integration platform data elements. Combine the analysis results with the data differences to determine whether data elements need to be converted, and establish corresponding mapping rules for elements that need to be converted. Review unit: Review data sources, identify the types of conflicts that may occur during data integration, analyze the root causes of the conflicts, and develop corresponding solutions based on the root causes; Integration unit: collects corresponding department data according to the solution, converts the department data into platform data corresponding to the integration platform based on mapping rules and related connections, divides the platform data according to department names, and determines internal supply chain or external supply chain; The risk point module includes: Process unit: collects node information of the internal supply chain, determines the supply chain process based on the node information, and obtains relevant operation details and historical performance data; Key Node Unit: Determine the business objectives that need to be supported by internal supply chain management, conduct a key assessment of the current status of the internal supply chain in combination with business objectives, relevant operational details and historical performance data, and identify key nodes in the internal supply chain; Performance evaluation unit: evaluates the efficiency of the internal supply chain operation according to the key nodes, identifies the performance status of the internal supply chain, and uses pre-set key performance evaluation indicators to diagnose the overall and local performance of the internal supply chain; Risk point determination unit: based on the diagnosis results, the internal supply chain risk points are determined; The low efficiency point module comprises: Starting point unit: List all suppliers of fuel-related products and related downstream products, and determine the starting point of the external supply chain, where the suppliers include direct suppliers and indirect suppliers; Supply Chain Determination Unit: Evaluate the carriers of fuel transportation and the distributors responsible for regional fuel allocation, determine the process lines and intermediate points of the external supply chain, determine the end point of the external supply chain according to the end users, and then determine the external supply chain; Risk level unit: formulate external supply chain risk assessment standards from two dimensions: the possibility of risk occurrence and the degree of impact caused by the risk, conduct risk assessment on the external supply chain, determine the risks that may affect each link of the external supply chain, and determine the internal and external environmental causes corresponding to each risk, and then determine the risk level of each link; Performance indicator unit: According to the operational data of each link in the external supply chain, determine the characteristics of the corresponding link, and determine the key performance indicators of the corresponding link based on the characteristics of the link and the risk level; Inefficiency low point unit: compare the operation data of each link with the corresponding key performance indicators to determine the inefficiency points; The policy module comprises: Probability unit: Calculate the probability of the corresponding point occurring based on the relevant data of each risk point and inefficiency point; Matrix unit: Evaluate the specific impact of each risk point and inefficiency point, establish a risk matrix, and map each risk point and inefficiency point onto the risk matrix based on the results of probability calculation and impact analysis; Priority unit: Assign a quantitative score to each risk point and inefficiency point, and determine the priority of each risk point and inefficiency point; Improvement Unit: Develop improvement measures for each high-risk point and low-efficiency point based on priority.

2. A coordinated fuel interaction management system according to claim 1, characterized in that: Performance evaluation unit, including: Performance determination block: Determine the key performance indicators that need to be tracked and evaluated at each key node based on the internal supply chain, collect the actual operation data of each key node, and determine the actual performance of the corresponding key node; Efficiency block: compares the actual performance of each key node with the fuel industry standard to derive the operating efficiency of the internal supply chain; Area block: Determine the scope and dimension of identification according to the key nodes, determine the performance status of the internal supply chain based on the scope and dimension combined with the comparison results of the efficiency block, and obtain the strong and weak areas; Diagnostic block: The operational efficiency, strong and weak areas and pre-set key performance evaluation indicators are used to conduct root cause analysis on inefficient points and weak areas of operational efficiency, determine the specific causes of poor performance, and diagnose the overall and local performance of the internal supply chain based on the specific causes.

3. A coordinated fuel interaction management system according to claim 1, characterized in that: Risk level unit, including: Calculation block: Determine the risk level of the corresponding link based on the operational data of each link and combining internal and external environmental factors; ； in, Indicates the risk level; , , and They represent the possible level weight coefficient, the impact level weight coefficient, the recovery difficulty level weight coefficient and the detection difficulty level weight coefficient respectively; Indicates the possible level, express The number of inefficiencies that occurred during the time period; Indicates the level of impact; express The extent of the negative impact of inefficiencies during the time period; Indicates the level of difficulty in recovery; It indicates the time it takes for the supply chain to return to normal after an inefficiency occurs; represents the recovery cost; Indicates the level of detection difficulty; Indicates the monitoring effectiveness of the corresponding low efficiency point; Indicates transparency of monitoring data; It represents the adjustment function of the influence factor of the external environment impact adjustment data x and the internal environment impact adjustment data y on the low efficiency point.

4. A coordinated fuel interaction management system according to claim 1, characterized in that: The matrix unit also includes: According to the probability of occurrence of risk points and inefficiency points as the X-axis and the influencing factors as the Y-axis, the positions of the corresponding risk points and inefficiency points in the risk matrix are located.

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