Industrial field production decision-making system and method based on intelligent decision-making model

Abstract

The invention provides an industrial field production decision-making system and method based on an intelligent decision-making model, and the system comprises an IBP consistency plan module which is used for supporting the generation of an integrated business plan group; a plurality of different strategy plans are set for comparison, and plan decision making is assisted; the intelligent main plan decision-making module is used for supporting constraint configuration at least including productivity and materials, generating different target-oriented main plan versions and making a decision on an optimized production plan; the intelligent production planning module is used for supporting configuration of demand plans of different levels and generating a production line scheduling plan with limited capability; the system is also used for supporting visual display of a production line scheduling plan result; and the order full life cycle management module is used for measuring and calculating an order delivery plan and generating an order delivery time report by taking the order demand as input and the capacity and the material as constraints. According to the invention, an intelligent decision technology is introduced to solve the production decision problem in the industrial field.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent production decision-making in the industrial field, and in particular to an industrial production decision-making system and method based on an intelligent decision-making model. Background Art

[0002] In the process of digitalization and intelligentization of today's manufacturing industry, the production environment has become increasingly complex and the amount of data has increased significantly. Traditional production decision-making methods are becoming increasingly incapable of coping with such rapidly changing and volatile production conditions. Traditional methods often rely on manual analysis and empirical judgment, which makes it difficult to efficiently process large and diverse data, which not only affects the accuracy of decision-making, but also limits the speed and flexibility of response.

[0003] Various data in the production process, including equipment status, production progress, quality indicators, etc., are collected in real time through sensors and networks, forming a huge data stream. The high frequency and complexity of these data streams require the decision-making system to not only be able to process and analyze quickly, but also have a high degree of intelligence, so as to adjust production strategies in a timely manner, optimize resource allocation, and improve production efficiency.

[0004] Therefore, traditional decision-making methods urgently need to be upgraded, and the introduction of intelligent decision-making technology has become an important direction for solving production decision-making problems. Summary of the invention

[0005] One of the purposes of the present invention is to provide an industrial production decision system based on an intelligent decision-making model, aiming to solve the above-mentioned technical problems.

[0006] An industrial production decision system based on an intelligent decision model provided by an embodiment of the present invention uses the intelligent decision model and includes:

[0007] IBP consistency planning module is used to support the generation of integrated business plan groups; it is also used to support the setting of multiple different strategic plans for comparison and assist in planning decisions;

[0008] Intelligent master plan decision module, used to support at least capacity and material constraint configuration, generate different goal-oriented master plan versions, and make decisions to optimize production plans;

[0009] Intelligent production planning module, which is used to support the configuration of demand plans at different levels and generate production line scheduling plans with limited capacity; it is also used to support the visual display of production line scheduling results;

[0010] The order life cycle management module is used to calculate the order delivery plan and generate order delivery period reports based on order demand as input and production capacity and materials as constraints.

[0011] Preferably, the IBP consistency planning module includes:

[0012] The market supply and demand balance unit is used to unify the command of demand and supply operations based on the balance of demand and supply plans;

[0013] The planning efficiency improvement unit is used to quickly respond to and generate a master production plan based on the consensus needs of each department and around the set unified goals;

[0014] The team strategy unification unit is used to provide a comparison of the planned results of at least the indicators of finance, sales, procurement, and inventory, and to visualize the comparison results;

[0015] Inventory monitoring assurance unit used to make commitments based on established demand.

[0016] Preferably, the intelligent master plan decision module includes:

[0017] Multi-level factory collaboration unit, used to support the development of multi-factory collaborative production plans and allow inter-factory stock transfers;

[0018] Internal and external resource integration unit, used to integrate internal warehouse, procurement, and demand departments, while formulating production plans based on the capabilities of external suppliers;

[0019] Time dimension unit, used to support production planning in multiple time dimensions such as day, week, ten-day, month, etc.

[0020] The customer response unit is used to generate production plans based on operations optimization algorithms, match sales order requirements, quickly calculate order delivery plans, and respond to customers.

[0021] Preferably, the intelligent production planning module includes:

[0022] The planning unit is used to schedule production intelligently based on limited capacity and combined with different optimization goals, and supports multi-level and multi-version plan comparison;

[0023] Parameters configuration unit, which allows customization of planning logic parameters;

[0024] The exception response unit is used to allow the addition of production lines for emergencies;

[0025] Demand fulfillment units are used for on-demand production while taking into account supply chain capacity constraints.

[0026] Preferably, the order life cycle management module includes:

[0027] The order calculation unit is used to pre-build an algorithm model, taking sales order requirements as input to solve the order satisfaction situation;

[0028] The order commitment quantitative unit is used to reasonably match orders and generate order delivery plans based on limited production capacity and material supply conditions;

[0029] The order cycle monitoring unit is used to control the entire life cycle of sales orders and track each link including planning, procurement, production, and delivery;

[0030] The order abnormality warning unit is used to calculate and output production capacity gaps and material shortages at the same time, and guide production capacity adjustments and material procurement plans.

[0031] An industrial production decision method based on an intelligent decision model provided by an embodiment of the present invention uses the intelligent decision model and includes:

[0032] The IBP consistency plan module supports the generation of an integrated business plan group and the comparison of multiple different strategic plans to assist in planning decisions.

[0033] The intelligent master plan decision module supports at least capacity and material constraint configuration, generates different goal-oriented master plan versions, and makes decisions to optimize production plans;

[0034] The intelligent production planning module supports the configuration of demand plans at different levels and generates production line scheduling plans with limited capacity. It is also used to support the visual display of production line scheduling results.

[0035] The order life cycle management module uses order demand as input and production capacity and materials as constraints to calculate the order delivery plan and generate an order delivery report.

[0036] Preferably, the IBP consistency plan module supports the generation of an integrated business plan group, and also supports the setting of multiple different strategic plans for comparison to assist in planning decisions, including:

[0037] The market supply and demand balancing unit uses the balance of demand and supply plans as the basis to unify the command of demand and supply operations;

[0038] The planning efficiency improvement unit generates a master production plan based on the consensus needs of various departments and around the set unified goals in a quick response;

[0039] Provide a comparison of planned results for at least financial, sales, purchasing, and inventory indicators through the team strategy unified unit, and visualize the comparison results;

[0040] Inventory monitoring ensures that units are committed based on established demand.

[0041] Preferably, the intelligent master plan decision module supports at least capacity and material constraint configuration, generates different goal-oriented master plan versions, and makes decisions to optimize the production plan, including:

[0042] Support the development of multi-factory collaborative production plans through multi-level factory collaboration units, allowing inter-factory inventory transfers;

[0043] Integrate internal warehouses, procurement, and demand departments through internal and external resource integration units, and formulate production plans based on the capabilities of external suppliers;

[0044] The time dimension unit supports the formulation of production plans in multiple time dimensions such as day, week, ten-day, month, etc.

[0045] Through the production plan generated by the customer response unit based on the operations optimization algorithm, sales order demand is matched, the order delivery plan is quickly calculated, and customers are responded to.

[0046] Preferably, the intelligent production planning module supports configuration of demand plans at different levels to generate production line scheduling plans with limited capacity; it is also used to support visual display of production line scheduling results, including:

[0047] The planning unit takes limited capacity as the premise, combines different optimization goals, and intelligently schedules production, supporting multi-level and multi-version plan comparison;

[0048] The parameter configuration unit allows customization of planning logic parameters;

[0049] The exception response unit allows the addition of unexpected events to the production line;

[0050] Produce on demand through demand fulfillment units while taking into account supply chain capacity constraints.

[0051] Preferably, the order lifecycle management module uses order demand as input, production capacity and materials as constraints, calculates the order delivery plan, and generates an order delivery report, including:

[0052] The order calculation unit prefabricates the algorithm model, takes the sales order demand as input, and solves the order satisfaction situation;

[0053] Through the order commitment quantification unit, with limited production capacity as the constraint, combined with the material supply situation, reasonably match orders and generate order delivery plans;

[0054] The order cycle monitoring unit fully controls the entire life cycle of sales orders and tracks each link including planning, procurement, production, and delivery;

[0055] The order abnormality warning unit calculates and outputs the production capacity gap and material shortage situation at the same time, guiding the production capacity adjustment and material procurement plan.

[0056] This application has achieved the following beneficial effects:

[0057] The IBP consistency planning module achieves unified coordination of various departments and links of the enterprise through functions such as market supply and demand balance, planning efficiency improvement, team strategy unification and inventory monitoring. Under the set unified goal, this module can quickly respond to market changes, optimize resource allocation, and improve the understanding and recognition of planning results by various departments through visualization tools, thereby improving overall planning efficiency and decision-making accuracy.

[0058] The intelligent master plan decision module helps enterprises formulate more accurate and flexible production plans through multi-level factory collaboration, internal and external resource integration, time dimension support and customer response functions. This module allows enterprises to optimize resource allocation in a multi-factory environment, integrate internal and external resources, support production plan formulation in different time dimensions, and quickly adjust production plans according to customer needs, thereby improving the flexibility of production plans and customer responsiveness.

[0059] The intelligent production planning module supports enterprises to conduct intelligent production scheduling under limited production capacity through functions such as planning, parameter configuration, abnormal response and demand satisfaction. This module allows users to customize planning logic parameters and flexibly respond to unexpected events on the production line, thereby optimizing production scheduling, reducing production costs, ensuring on-demand production, and improving the overall efficiency of the supply chain.

[0060] The order life cycle management module provides full support from order measurement, order commitment quantification, order cycle monitoring to order abnormality warning. Through this module, enterprises can accurately measure the order fulfillment, reasonably match production capacity and material supply, track the order life cycle in real time, and timely warn and adjust production plans and material procurement. This comprehensive order management capability significantly improves the company's order fulfillment capabilities, reduces delivery delays, and enhances customer satisfaction.

[0061] Through the close collaboration and integrated operation of the above modules, this system has achieved the introduction of intelligent decision-making technology to solve production decision-making problems in the industrial field, which can effectively improve the company's production planning and supply chain management level, and provide strong support for the company in a highly competitive market environment.

[0062] 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.

[0063] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] 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:

[0065] Figure 1 Schematic diagram of an industrial production decision system based on an intelligent decision model in an embodiment of the present invention;

[0066] Figure 2 Schematic diagram of the IBP consistency plan module structure in an embodiment of the present invention;

[0067] Figure 3 Schematic diagram of the structure of the intelligent master plan decision module in an embodiment of the present invention;

[0068] Figure 4 A schematic diagram of the structure of an intelligent production planning module in an embodiment of the present invention;

[0069] Figure 5 Schematic diagram of the order life cycle management module structure in an embodiment of the present invention. DETAILED DESCRIPTION

[0070] 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.

[0071] The embodiment of the present invention provides an industrial production decision system based on an intelligent decision model, using an intelligent decision model, such as Figure 1 As shown, including:

[0072] IBP consistency plan module 1 is used to support the generation of an integrated business plan group; it is also used to support the setting of multiple different strategic plans for comparison and assist in planning decisions;

[0073] Intelligent master plan decision module 2, used to support the constraint configuration of at least production capacity and materials, generate master plan versions with different goal orientations, and make decisions to optimize production plans;

[0074] Intelligent production planning module 3 is used to support the configuration of demand plans at different levels and generate production line scheduling plans with limited capacity; it is also used to support the visual display of production line scheduling results;

[0075] The order life cycle management module 4 is used to calculate the order delivery plan and generate an order delivery report based on order demand as input and production capacity and materials as constraints.

[0076] The working principle and beneficial effects of the above technical solution are:

[0077] When building an intelligent decision-making model, a large amount of experience in industrial production decision-making can be used as training samples to train the neural network until convergence to obtain an intelligent decision-making model.

[0078] The IBP consistency planning module achieves unified coordination of various departments and links of the enterprise through functions such as market supply and demand balance, planning efficiency improvement, team strategy unification and inventory monitoring. Under the set unified goal, this module can quickly respond to market changes, optimize resource allocation, and improve the understanding and recognition of planning results by various departments through visualization tools, thereby improving overall planning efficiency and decision-making accuracy.

[0079] The intelligent master plan decision module helps enterprises formulate more accurate and flexible production plans through multi-level factory collaboration, internal and external resource integration, time dimension support and customer response functions. This module allows enterprises to optimize resource allocation in a multi-factory environment, integrate internal and external resources, support production plan formulation in different time dimensions, and quickly adjust production plans according to customer needs, thereby improving the flexibility of production plans and customer responsiveness.

[0080] The intelligent production planning module supports enterprises to conduct intelligent production scheduling under limited production capacity through functions such as planning, parameter configuration, abnormal response and demand satisfaction. This module allows users to customize planning logic parameters and flexibly respond to unexpected events on the production line, thereby optimizing production scheduling, reducing production costs, ensuring on-demand production, and improving the overall efficiency of the supply chain.

[0081] The order life cycle management module provides full support from order measurement, order commitment quantification, order cycle monitoring to order abnormality warning. Through this module, enterprises can accurately measure the order fulfillment, reasonably match production capacity and material supply, track the order life cycle in real time, and timely warn and adjust production plans and material procurement. This comprehensive order management capability significantly improves the company's order fulfillment capabilities, reduces delivery delays, and enhances customer satisfaction.

[0082] Through the close collaboration and integrated operation of the above modules, this system has achieved the introduction of intelligent decision-making technology to solve production decision-making problems in the industrial field, which can effectively improve the company's production planning and supply chain management level, and provide strong support for the company in a highly competitive market environment.

[0083] In one embodiment, Figure 2 As shown, IBP consistency plan module 1 includes:

[0084] The market supply and demand balance unit 11 is used to unify the command of the operation of demand and supply based on the balance of demand and supply plans;

[0085] The planning efficiency improvement unit 12 is used to generate a master production plan based on the consensus needs of various departments and around the set unified goals in a quick response;

[0086] The team strategy unification unit 13 is used to provide a comparison of the planning results of at least the indicators of finance, sales, procurement, and inventory, and to visualize the comparison results;

[0087] The inventory monitoring and assurance unit 14 is used to make commitments based on established demand.

[0088] The working principle and beneficial effects of the above technical solution are:

[0089] The market supply and demand balance unit 11 performs algorithmic processing based on the balance of demand and supply plans, and ensures the coordination between the two by unified command of the operation of demand and supply. This method can reduce resource waste, optimize production scheduling, improve overall supply chain efficiency, achieve accurate inventory management and more effective production arrangements, and reduce the risk of excess or shortage.

[0090] The planning efficiency improvement unit 12 generates a master production plan based on the consensus needs of each department and around the set unified goal. This unit uses a rapid response mechanism to ensure that the production plan can promptly reflect the needs of each department and adjust quickly when changes occur, shortening the plan generation time, improving production flexibility, and improving the efficiency of collaboration among departments.

[0091] Team Strategy Unification Unit 13 provides a comparison of planning results involving financial, sales, procurement, inventory and other indicators, and displays them visually. This comparison and visualization can help the team quickly identify potential problems and improvement opportunities, enhance decision-making transparency, support cross-departmental collaboration, and improve the ability to monitor the effectiveness of plan execution.

[0092] The inventory monitoring and assurance unit 14 makes inventory commitments based on established demand to ensure that the inventory level can meet actual demand. This unit continuously monitors and adjusts inventory levels to prevent insufficient or excessive inventory, optimize inventory costs, reduce inventory backlogs, and improve the responsiveness and reliability of the supply chain.

[0093] In one embodiment, Figure 3 As shown, the intelligent master plan decision module 2 includes:

[0094] Multi-level factory collaboration unit 21, used to support the development of multi-factory collaborative generation plans and allow inter-factory stock transfers;

[0095] Internal and external resource integration unit 22 is used to integrate internal warehouse, procurement, and demand departments, and formulate production plans based on the capabilities of external suppliers;

[0096] Time dimension unit 23, used to support production planning in multiple time dimensions such as day, week, ten-day, month, etc.;

[0097] The customer response unit 24 is used to generate a production plan based on the operations optimization algorithm, match sales order requirements, quickly calculate the order delivery plan, and respond to customers.

[0098] The working principle and beneficial effects of the above technical solution are:

[0099] The multi-level factory coordination unit 21 optimizes the overall production resource allocation by formulating a multi-factory coordination plan and allowing inventory transfers between factories. This approach can improve the coordination and resource utilization efficiency between factories, reduce inventory redundancy, improve production flexibility, and enhance the overall responsiveness of the supply chain.

[0100] Internal and external resource integration unit 22 integrates internal warehouses, procurement and demand departments, and takes external supplier capabilities as constraints to develop a comprehensive production plan. This integration ensures the full utilization of resources and the feasibility of production plans, improves the accuracy of production plans and the feasibility of implementation, reduces resource conflicts, and improves the collaborative efficiency of the supply chain.

[0101] The time dimension unit 23 supports the formulation of production plans in multiple time dimensions such as day, week, ten-day, month, etc. This flexible time dimension supports helping enterprises adjust production arrangements according to different demand cycles. Beneficial effects include enhancing the adaptability of production plans, improving the ability to respond to demand fluctuations, and optimizing production scheduling.

[0102] The customer response unit 24 generates production plans using operations optimization algorithms, and based on these plans, quickly calculates the delivery time of a single order, responds to customer needs in a timely manner, shortens delivery cycles, improves customer satisfaction, and enhances the company's market competitiveness.

[0103] In one embodiment, Figure 4 As shown, the intelligent production planning module 3 includes:

[0104] Planning unit 31 is used to intelligently schedule production based on limited capacity and combined with different optimization goals, and supports multi-level and multi-version plan comparison;

[0105] A parameter configuration unit 32, for allowing customization of planning logic parameters;

[0106] Abnormal response unit 33, used to allow the addition of production lines for emergencies;

[0107] The demand fulfillment unit 34 is used for on-demand production while taking into account supply chain capacity constraints.

[0108] The working principle and beneficial effects of the above technical solution are:

[0109] The planning unit 31 generates plans through intelligent production scheduling based on limited production capacity and different optimization goals, and supports multi-level and multi-version plan comparison. This method can optimize resource allocation, improve production scheduling efficiency, optimize the utilization of production resources in a complex production environment, and can flexibly adjust and compare different planning schemes.

[0110] The parameter configuration unit 32 allows the user to customize the parameters of the planning logic to adapt to different production requirements and optimization goals. This customization function provides flexibility, allowing the plan to more accurately meet the actual situation, improve the applicability and accuracy of the plan, and enhance the flexibility of the system.

[0111] The exception response unit 33 allows users to add and handle emergencies on the production line, ensuring that the production plan can cope with unexpected situations, enhancing the robustness of the production plan, and improving the system's ability to respond to emergencies, thereby reducing the negative impact on production.

[0112] The demand satisfaction unit 34 produces according to actual demand while taking into account the capacity constraints of the supply chain, ensuring the coordination of production and supply chain, improving the accuracy of production plans, optimizing the allocation of supply chain resources, and meeting customer needs while maintaining supply chain stability.

[0113] In one embodiment, Figure 5 As shown, the order life cycle management module 4 includes:

[0114] The order calculation unit 41 is used to prefabricate an algorithm model, take the sales order demand as input, and solve the order satisfaction;

[0115] The order commitment quantification unit 42 is used to reasonably match orders and generate order delivery plans based on limited production capacity and material supply conditions;

[0116] The order cycle monitoring unit 43 is used to control the entire life cycle of sales orders and track each link such as planning, procurement, production, and delivery;

[0117] The order abnormality warning unit 44 is used to calculate and output the capacity gap and material shortage at the same time, and guide the capacity adjustment and material procurement plan.

[0118] The working principle and beneficial effects of the above technical solution are:

[0119] The order calculation unit 41 uses a pre-made algorithm model to evaluate the order fulfillment by inputting sales order requirements, which can help predict whether the order can be completed on time, improve the accuracy and efficiency of order processing, and identify possible delivery problems in advance. The pre-made algorithm model can be set in advance by the technician according to actual needs.

[0120] The order commitment quantification unit 42 combines limited production capacity and material supply conditions to reasonably match orders, thereby generating a specific order delivery plan, optimizing production capacity utilization, and ensuring reasonable allocation and timely delivery of orders.

[0121] The order cycle monitoring unit 43 tracks the entire life cycle of sales orders, including planning, procurement, production and delivery, to improve visibility and control over the order execution process and to identify and resolve potential problems in a timely manner.

[0122] The order abnormality warning unit 44 is used to measure the capacity gap and material shortage, and provide warning information to guide subsequent capacity adjustment and material procurement plans, identify potential production and supply chain problems in advance, optimize adjustment strategies, and reduce the risk of production interruption.

[0123] In one embodiment, the industrial production decision system based on the intelligent decision model further includes:

[0124] Auxiliary modules for:

[0125] Based on multimodal data, a decision supervision visualization model is constructed; wherein the multimodal data at least includes: working status information of the IBP consistency plan module 1, the intelligent master plan decision module 2, the intelligent production plan module 3 and the order full life cycle management module 4; the working status information includes: working status, working progress, working results, etc. For example, taking the IBP consistency plan module 1 as an example, the working status is the number of integrated business plan groups generated, and the working progress is the generation progress of the integrated business plan groups, etc.; based on multimodal data, a decision supervision visualization model is constructed, and the decision supervision visualization model can visualize the multimodal data to the supervisor. Specifically, when constructing the decision supervision visualization model, the technical personnel can pre-construct the model template and construct it based on the template;

[0126] When a supervisor views the supervisory visualization model, the viewing perspective sequence of the supervisor is continuously recorded in real time; a supervisor is a person who supervises the work of intelligent decision-making. When a supervisor views the supervisory visualization model, a viewing perspective sequence is generated, and the viewing perspective sequence includes the viewing perspectives of the supervisor who viewed the supervisory visualization model in history;

[0127] When the viewing perspective sequence does not change within the first time period or the newly added viewing perspective meets the first perspective triggering condition, each viewing perspective in the latest viewing perspective sequence within the second time period is traversed in sequence; when the viewing perspective sequence does not change within the first time period or the newly added viewing perspective meets the first perspective triggering condition, it means that the supervisor may want to implement specific supervision and management measures at this time, and each viewing perspective in the latest viewing perspective sequence within the second time period is traversed in sequence;

[0128] If the i-th viewing angle in the latest viewing angle sequence traversed meets the second viewing angle trigger condition, the first partial viewing angle sequence from the ij-th viewing angle to the i-th viewing angle is intercepted from the latest viewing angle sequence; the size of j is positively correlated with the total number of conditions that the viewing angle meets the first viewing angle trigger condition and the i-th viewing angle meets the second viewing angle trigger condition; if the i-th viewing angle in the latest viewing angle sequence traversed meets the second viewing angle trigger condition, it means that the supervisor wants to implement the supervision and management measures at this time and needs to be assisted, and the first partial viewing angle sequence from the ij-th viewing angle to the i-th viewing angle is intercepted from the latest viewing angle sequence; the more the total number of conditions that the viewing angle meets the first viewing angle trigger condition and the i-th viewing angle meets the second viewing angle trigger condition, the greater the overall degree to which the supervisor wants to implement the supervision and management measures, the more accurate assistance is needed, and the more viewing behaviors that can be used as auxiliary basis are generated, and the more viewing angles need to be intercepted, the larger j is; ij≥1;

[0129] Extracting features from the first partial view sequence to obtain a sequence feature set; the features in the sequence feature set include: the visual content type of each viewing view in the first partial view sequence, the generation order of each viewing view, etc.;

[0130] Determine the target adjustment strategy from the visualization model adjustment strategy library; the first matching degree between the standard sequence feature set of the target adjustment strategy and the sequence feature set exceeds the first matching degree threshold; the sequence feature set will reflect how the supervisor wants to implement the supervision and management measures, and there is a corresponding target adjustment strategy in the visualization model adjustment strategy library; the first matching degree threshold may be 80%; the standard sequence feature set is a sequence feature set representing that the target adjustment strategy is suitable for assisting the supervisor at present, for example: the target adjustment strategy is to display the feedback information of all production sites, and the features in the standard sequence feature set are to successively view the adverse reactions of the production site through viewing perspectives, etc. When the first matching degree between the standard sequence feature set and the sequence feature set exceeds the first matching degree threshold, it means that the target adjustment strategy is suitable;

[0131] Based on the target adjustment strategy, the supervision visualization model viewed by the supervisor is continuously adjusted during the third time period, and the supervision management strategy decided by the supervisor is received; based on the target adjustment strategy, the supervision visualization model viewed by the supervisor is continuously adjusted during the third time period, and the adjusted supervision visualization model can display content that has a positive and active auxiliary effect on the supervisor's specific implementation of supervision management measures; during the third time period, after receiving assistance, the supervisor will also decide on the supervision management strategy; the supervision management strategy is the supervision management measures specifically implemented by the supervisor;

[0132] Execute supervisory management strategies online;

[0133] The first time period is the most recent time period of the first preset duration in history; the first preset duration may be 200 seconds;

[0134] The second time period is after the first time period and is separated from the first time period by a preset time interval, and the length of the second time period is the second preset time length; the preset time interval may be 50 seconds; it is preliminarily determined in the first time period that the supervisor may want to implement specific supervision and management measures, and the preset time interval is set as the waiting time, so as to facilitate further determination of the specific circumstances in which the supervisor wants to implement specific supervision and management measures in the second time period;

[0135] The third time period is after the second time period and adjacent to the second time period; the duration of the third time period is a third preset duration; the third preset duration may be 300 seconds;

[0136] The first-person perspective trigger conditions include:

[0137] The newly added viewing perspective switching feature matches the standard perspective switching feature; the standard perspective switching feature is a perspective switching feature that represents that the supervisor may want to implement specific supervision and management measures. For example, the standard perspective feature is that the supervisor frequently switches between two perspectives, indicating that the supervisor may be comparing content and may want to implement specific supervision and management measures.

[0138] and / or,

[0139] The visual content features of the newly added viewing perspectives match the standard visual content features; the standard visual content features are visual content features that represent specific supervisory management measures that supervisors may want to implement, for example: the standard visual content features are information on tracking work progress, indicating that supervisors may be tracking work progress and may want to implement specific supervisory management measures;

[0140] and / or,

[0141] The second matching degree between the second local perspective sequence in the viewing perspective sequence and the third local perspective sequence formed by the newly added viewing perspective exceeds the second matching degree threshold; the second local perspective sequence is a local sequence in the viewing perspective sequence, formed by multiple viewing perspectives; the second matching degree threshold may be 75%; the continuous generation of viewing perspectives represents the supervisory ideas of the supervisor to a certain extent, and when the second matching degree between the second local perspective sequence in the viewing perspective sequence and the third local perspective sequence formed by the newly added viewing perspective exceeds the second matching degree threshold, it indicates that the supervisor has relatively similar repeated supervision ideas and may want to implement specific supervision management measures;

[0142] The second perspective trigger conditions include:

[0143] The perspective retention feature of the i-th viewing perspective matches the standard perspective retention feature; the standard perspective retention feature is a perspective retention feature that represents the supervisory personnel's actual intention to implement specific supervision and management measures. For example, if the perspective retention feature is that the total duration of the perspective being fixed exceeds 20 seconds, it means that the supervisory personnel is continuously thinking based on a certain viewing perspective and actually wants to implement specific supervision and management measures.

[0144] and / or,

[0145] The i-th viewing perspective is the last perspective of the fourth local viewing perspective sequence in the latest viewing perspective sequence; the time interval between viewing perspectives in pairs in the fourth local viewing perspective sequence does not exceed the interval threshold. The fourth local viewing perspective sequence is a local sequence of a part in the latest viewing perspective sequence, and is also formed by multiple viewing perspectives. The interval threshold can be 10 seconds; the time interval between viewing perspectives in pairs in the fourth local viewing perspective sequence does not exceed the interval threshold, indicating that the fourth local viewing perspective sequence is continuously generated by the user in a short period of time, indicating that the supervisor knows what he wants to see and has clear ideas, and is more likely to want to implement specific supervision and management measures.

[0146] In order to ensure the orderliness and stability of intelligent decision-making work, it is necessary to arrange supervisors to supervise. The embodiment of the present invention introduces a decision supervision visualization model, which is convenient for supervisors to view the decision-making work situation intuitively and comprehensively; then, when the viewing perspective sequence does not change within the first time period or the newly added viewing perspective meets the first perspective trigger condition, the condition setting is introduced to accurately determine the time for the auxiliary supervisor to supervise; then, the second perspective trigger condition is introduced to further accurately determine the time for the auxiliary supervisor to supervise; then, the first local sequence is introduced to quickly determine the target adjustment strategy, adjust the decision supervision visualization model, and realize the supervision assistance for the supervisor, which is particularly humane and intelligent, and improves the work efficiency of the supervisor; secondly, the reasonable setting of different time periods enables the system to have an efficient and intelligent auxiliary process.

[0147] The embodiment of the present invention provides an industrial production decision-making method based on an intelligent decision-making model, using the intelligent decision-making model, including:

[0148] The IBP consistency plan module supports the generation of an integrated business plan group and the comparison of multiple different strategic plans to assist in planning decisions.

[0149] The intelligent master plan decision module supports at least capacity and material constraint configuration, generates different goal-oriented master plan versions, and makes decisions to optimize production plans;

[0150] The intelligent production planning module supports the configuration of demand plans at different levels and generates production line scheduling plans with limited capacity. It is also used to support the visual display of production line scheduling results.

[0151] The order life cycle management module uses order demand as input and production capacity and materials as constraints to calculate the order delivery plan and generate an order delivery report.

[0152] The IBP consistency plan module supports the generation of an integrated business plan group and the comparison of multiple different strategic plans to assist in planning decisions, including:

[0153] The market supply and demand balancing unit uses the balance of demand and supply plans as the basis to unify the command of demand and supply operations;

[0154] The planning efficiency improvement unit generates a master production plan based on the consensus needs of various departments and around the set unified goals in a quick response;

[0155] Provide a comparison of planned results for at least financial, sales, purchasing, and inventory indicators through the team strategy unified unit, and visualize the comparison results;

[0156] Inventory monitoring ensures that units are committed based on established demand.

[0157] The intelligent master plan decision module supports at least capacity and material constraint configuration, generates different goal-oriented master plan versions, and makes decisions to optimize production plans, including:

[0158] Support the development of multi-factory collaborative production plans through multi-level factory collaboration units, allowing inter-factory inventory transfers;

[0159] Integrate internal warehouses, procurement, and demand departments through internal and external resource integration units, and formulate production plans based on the capabilities of external suppliers;

[0160] The time dimension unit supports the formulation of production plans in multiple time dimensions such as day, week, ten-day, month, etc.

[0161] Through the production plan generated by the customer response unit based on the operations optimization algorithm, sales order demand is matched, the order delivery plan is quickly calculated, and customers are responded to.

[0162] The intelligent production planning module supports the configuration of demand plans at different levels and generates production line scheduling plans with limited capacity. It is also used to support the visualization of production line scheduling results, including:

[0163] The planning unit takes limited capacity as the premise, combines different optimization goals, and intelligently schedules production, supporting multi-level and multi-version plan comparison;

[0164] The parameter configuration unit allows customization of planning logic parameters;

[0165] The exception response unit allows the addition of unexpected events to the production line;

[0166] Produce on demand through demand fulfillment units while taking into account supply chain capacity constraints.

[0167] The order lifecycle management module uses order demand as input and production capacity and materials as constraints to calculate order delivery plans and generate order delivery reports, including:

[0168] The order calculation unit prefabricates the algorithm model, takes the sales order demand as input, and solves the order satisfaction situation;

[0169] Through the order commitment quantification unit, with limited production capacity as the constraint, combined with the material supply situation, reasonably match orders and generate order delivery plans;

[0170] The order cycle monitoring unit fully controls the entire life cycle of sales orders and tracks each link including planning, procurement, production, and delivery;

[0171] The order abnormality warning unit calculates and outputs the production capacity gap and material shortage situation at the same time, guiding the production capacity adjustment and material procurement plan.

[0172] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An industrial production decision system based on an intelligent decision model, using an intelligent decision model, characterized in that: include: IBP consistency planning module, used to support the generation of integrated business plan groups; It is also used to support the comparison of multiple different strategic plans and assist in planning decisions; Intelligent master plan decision module, used to support at least capacity and material constraint configuration, generate different goal-oriented master plan versions, and make decisions to optimize production plans; Intelligent production planning module, which is used to support the configuration of different levels of demand planning and generate production line scheduling plans with limited capacity; It is also used to support the visual display of production line scheduling results; The order life cycle management module is used to calculate the order delivery plan and generate order delivery period reports based on order demand as input and production capacity and materials as constraints.

2. The industrial production decision system based on the intelligent decision model according to claim 1, characterized in that: The IBP consistency program modules include: The market supply and demand balance unit is used to unify the command of demand and supply operations based on the balance of demand and supply plans; The planning efficiency improvement unit is used to quickly respond to and generate a master production plan based on the consensus needs of each department and around the set unified goals; The team strategy unification unit is used to provide a comparison of the planned results of at least the indicators of finance, sales, procurement, and inventory, and to visualize the comparison results; Inventory monitoring assurance unit used to make commitments based on established demand.

3. The industrial production decision system based on the intelligent decision model according to claim 1, characterized in that: The intelligent master planning decision module includes: Multi-level factory collaboration unit, used to support the development of multi-factory collaborative production plans and allow inter-factory stock transfers; Internal and external resource integration unit, used to integrate internal warehouse, procurement, and demand departments, while formulating production plans based on the capabilities of external suppliers; Time dimension unit, used to support production planning in multiple time dimensions such as day, week, ten-day, month, etc. The customer response unit is used to generate production plans based on operations optimization algorithms, match sales order requirements, quickly calculate order delivery plans, and respond to customers.

4. The industrial production decision system based on the intelligent decision model according to claim 1, characterized in that: The intelligent production planning module includes: The planning unit is used to schedule production intelligently based on limited capacity and combined with different optimization goals, and supports multi-level and multi-version plan comparison; Parameters configuration unit to allow customization of planning logic parameters; The exception response unit is used to allow the addition of production lines for emergencies; Demand fulfillment units are used for on-demand production while taking into account supply chain capacity constraints.

5. The industrial production decision system based on the intelligent decision model according to claim 1, characterized in that: The order life cycle management module includes: The order calculation unit is used to pre-build an algorithm model, taking sales order requirements as input to solve the order satisfaction situation; The order commitment quantitative unit is used to reasonably match orders and generate order delivery plans based on limited production capacity and material supply conditions; The order cycle monitoring unit is used to control the entire life cycle of sales orders and track each link including planning, procurement, production, and delivery; The order abnormality warning unit is used to calculate and output the capacity gap and material shortage at the same time, and guide the capacity adjustment and material procurement plan.

6. An industrial production decision-making method based on an intelligent decision-making model, using an intelligent decision-making model, characterized in that: include: The IBP consistency plan module supports the generation of an integrated business plan group and the comparison of multiple different strategic plans to assist in planning decisions. The intelligent master plan decision module supports at least capacity and material constraint configuration, generates different goal-oriented master plan versions, and makes decisions to optimize production plans; The intelligent production planning module supports the configuration of different levels of demand plans and generates production line scheduling plans with limited capacity; It is also used to support the visual display of production line scheduling results; The order life cycle management module uses order demand as input and production capacity and materials as constraints to calculate the order delivery plan and generate an order delivery report.

7. The industrial production decision-making method based on the intelligent decision-making model according to claim 6 is characterized in that: The IBP consistency plan module supports the generation of an integrated business plan group and the comparison of multiple different strategic plans to assist in planning decisions, including: The market supply and demand balancing unit uses the balance of demand and supply plans as the basis to unify the command of demand and supply operations; The planning efficiency improvement unit generates a master production plan based on the consensus needs of various departments and around the set unified goals in a quick response; Provide a comparison of planned results for at least financial, sales, purchasing, and inventory indicators through the team strategy unified unit, and visualize the comparison results; Inventory monitoring ensures that units are committed based on established demand.

8. The industrial production decision-making method based on the intelligent decision-making model according to claim 6 is characterized in that: The intelligent master plan decision module supports at least capacity and material constraint configuration, generates different goal-oriented master plan versions, and makes decisions to optimize production plans, including: Support the development of multi-factory collaborative production plans through multi-level factory collaboration units, allowing inter-factory inventory transfers; Integrate internal warehouses, procurement, and demand departments through internal and external resource integration units, and formulate production plans based on the capabilities of external suppliers; The time dimension unit supports the formulation of production plans in multiple time dimensions such as day, week, ten-day, month, etc. Through the production plan generated by the customer response unit based on the operations optimization algorithm, sales order demand is matched, the order delivery plan is quickly calculated, and customers are responded to.

9. The industrial production decision-making method based on the intelligent decision-making model according to claim 6, characterized in that: The intelligent production planning module supports the configuration of different levels of demand plans and generates production line scheduling plans with limited capacity; It is also used to support the visual display of production line scheduling results, including: The planning unit takes limited capacity as the premise, combines different optimization goals, and intelligently schedules production, supporting multi-level and multi-version plan comparison; The parameter configuration unit allows customization of planning logic parameters; The exception response unit allows the addition of unexpected events to the production line; Produce on demand through demand fulfillment units while taking into account supply chain capacity constraints.

10. The industrial production decision-making method based on the intelligent decision-making model according to claim 6, characterized in that: The order lifecycle management module uses order demand as input and production capacity and materials as constraints to calculate order delivery plans and generate order delivery reports, including: The order calculation unit prefabricates the algorithm model, takes the sales order demand as input, and solves the order satisfaction situation; Through the order commitment quantification unit, with limited production capacity as the constraint, combined with the material supply situation, reasonably match orders and generate order delivery plans; The order cycle monitoring unit fully controls the entire life cycle of sales orders and tracks each link including planning, procurement, production, and delivery; The order abnormality warning unit calculates and outputs the production capacity gap and material shortage situation at the same time, guiding the production capacity adjustment and material procurement plan.

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