Component order wave management system

Abstract

The invention provides a component order wave management system, and relates to the technical field of data processing, and the system comprises an order data collection module; an order priority determination module; a wave content generation module; an inventory data acquisition module; the wave number content determination module is used for analyzing the demand quantity of the orders in each wave number, matching the demand quantity with the current inventory data, dynamically adjusting order distribution in the wave number, and generating an optimized wave number data set; a wave priority determination module; the wave scheduling module is used for determining the execution sequence of each wave in the optimized wave data set according to the wave priority data and the distribution resources, and dynamically adjusting distribution resource distribution in the wave execution process to form a wave management scheme; an anomaly detection module; an abnormality correction module; the data output module is used for outputting related data in the wave execution process and generating a wave execution report; according to the invention, the component order wave management efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a component order wave management system. Background Art

[0002] At present, component order wave management systems are widely used in industrial production and logistics management. Traditional order management systems usually arrange order waves in a manual or semi-automatic manner, combining inventory information and demand forecasts. These systems usually rely on manual input and monitoring to ensure timely processing and delivery of orders. This process mainly includes order splitting, allocation to different waves, and formulation of distribution plans, aiming to improve the accuracy and timeliness of material distribution. Common system architectures are usually composed of database management, task scheduling, and distribution modules, and wave planning is carried out through fixed rules.

[0003] However, existing technologies often face the problem of lack of flexibility in scheduling rules in practical applications, especially in cases of dynamic demand and large inventory fluctuations. For example, in the field of electronic product manufacturing, the procurement and distribution of components are usually affected by multiple factors such as supplier delivery dates and demand changes. In this scenario, traditional wave management systems often rely on static rules to allocate tasks, making it difficult to respond to sudden order changes in real time. For example, when a high-demand component needs to be replenished immediately, the system may not be able to adjust the wave quickly, causing delays, affecting the operating efficiency of the overall production line, and further causing delays in production plans. This lack of flexibility and instant adjustment makes the existing wave management system show certain shortcomings when responding to rapidly changing order demands. Summary of the invention

[0004] The purpose of the present invention is to provide a component order wave management system, aiming to solve the problems mentioned in the background technology.

[0005] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0006] A component order wave management system, the system comprising:

[0007] An order data collection module is used to collect order data in real time, where the order data includes the type, quantity, estimated delivery time and order source information of components;

[0008] The order priority determination module is used to analyze the delivery time, quantity and importance of the order based on the order data, evaluate the priority of each order, and generate order priority data;

[0009] The wave content generation module splits and classifies the orders into corresponding waves according to the order type, quantity and order priority data, and generates the initial wave data set;

[0010] The inventory data collection module is used to obtain the inventory status of components in real time by connecting with various warehouse systems, and to form an inventory data set based on the inventory levels of different components;

[0011] The wave content determination module is used to analyze the demand for orders in each wave and match them with the current inventory data based on the initial wave data set and the inventory data set to obtain matching score data, dynamically adjust the order allocation in the wave based on the matching score data, and generate an optimized wave data set;

[0012] A wave priority determination module is used to determine the wave priority according to the order priority data, the matching score data and the distribution resource requirements, and obtain the wave priority data;

[0013] The wave scheduling module is used to determine the execution order of each wave in the optimized wave data set according to the wave priority data and distribution resources, and dynamically adjust the distribution resource allocation during the wave execution process to form a wave management plan;

[0014] The anomaly detection module monitors order data, inventory data, and wave execution status in real time to identify anomalies that may occur during wave generation or execution, including insufficient inventory, order timeouts, and shortages of distribution resources.

[0015] The abnormality correction module is used to dynamically adjust the wave management plan according to the abnormal situation type;

[0016] The data output module is used to output relevant data during the wave execution process and generate a wave execution report; the relevant data includes order details, execution status, inventory changes and distribution resource allocation for each wave.

[0017] Preferably, the order priority determination module includes:

[0018] An order classification unit is used to classify orders into urgent orders and ordinary orders according to the delivery time of the orders, and obtain order classification data;

[0019] An order importance evaluation unit, used to evaluate the importance score of an order based on order source information and order quantity;

[0020] The priority allocation unit is used to calculate the priority score of the order according to the order classification data and the importance score, and generate the order priority data; the calculation formula of the order priority score is: ,in, For the The priority rating of the orders, For the The difference between the delivery deadline of an order and the current time, For the The number of components in an order, For the The importance score of each order, For the The delivery resource demand for each order, , , and is the adjustment coefficient; , For the The source rating of orders, , For the The number of components that need to be delivered in an order, For the The urgency score of the orders, , , and is the weight coefficient; , , and is the weight coefficient.

[0021] Preferably, the wave content generation module includes:

[0022] A preliminary splitting unit, used to divide an order into multiple sub-orders according to order classification data and their corresponding quantities;

[0023] A wave allocation unit is used to allocate sub-orders to different waves according to order priority data to generate an initial wave data set;

[0024] The wave capacity verification unit is used to check whether the total number of orders in each wave exceeds the preset wave capacity threshold, and split the orders that exceed the capacity into other waves.

[0025] Preferably, the inventory data collection module includes:

[0026] Data interface unit, used to collect inventory information of various components in real time through communication interfaces with multiple warehouse systems;

[0027] Data integration unit, used to aggregate and unify the format of inventory information to form an inventory data set;

[0028] The data updating unit is used to dynamically update the inventory data set according to the inventory changes collected in real time.

[0029] Preferably, the wave content determination module includes:

[0030] The matching calculation unit is used to calculate the matching score between the demand quantity of the orders in each wave and the current inventory data according to the initial wave data set, and obtain the matching score data; the calculation formula of the matching score is: ,in, For the The inventory matching score of each wave, For the The number of component types in a wave, For the Wave The order demand for components For the Wave The current inventory of the components, For the The inventory turnover time of each wave, For the The difference between the delivery deadline of the wave and the current time, is the adjustment coefficient;

[0031] A dynamic adjustment unit, used to dynamically adjust the order allocation in the wave according to the matching score data to generate an optimized wave data set, wherein the adjustment content includes removing orders with insufficient inventory or merging them into other waves;

[0032] The verification unit is used to check whether the order allocation results of the optimized wave data set meet the inventory conditions and wave capacity requirements.

[0033] Preferably, the wave priority determination module includes:

[0034] The data weighting unit is used to perform weighted calculation on each wave according to the order priority data, matching score data and distribution resource requirements to obtain a priority score. The calculation formula for the priority score of a wave is: ,in, For the The priority score of each wave, For the The number of orders in a wave, For the The actual usage of delivery resources for each order. For the The total time window allowed for each wave is , , and is the adjustment coefficient;

[0035] The priority sorting unit is used to sort and generate wave priority data according to the priority scores;

[0036] The adjustment unit is used to readjust the wave priority data when the wave priority ranking changes.

[0037] Preferably, the wave scheduling module includes:

[0038] An execution order determination unit, used for determining the execution order of each wave in the optimized wave data set according to the wave priority data and the distribution resources;

[0039] Resource allocation unit, used to dynamically allocate transport vehicles, delivery personnel and delivery equipment according to the execution requirements of each wave;

[0040] The resource monitoring unit is used to monitor the status of transport vehicles, delivery personnel, and delivery equipment as well as the execution of time windows in real time during the wave execution process, and provide dynamic adjustment suggestions to the resource allocation unit when resource allocation is insufficient or conflicting.

[0041] Preferably, the anomaly detection module comprises:

[0042] Data monitoring unit, used to monitor order data, inventory data and wave execution status in real time;

[0043] An abnormality determination unit, used to determine whether there is an abnormality of insufficient inventory, order timeout or shortage of distribution resources according to a preset abnormality determination threshold;

[0044] The exception reporting unit is used to generate an exception report when an abnormal situation is detected. The exception report includes the exception type and the number of the affected wave.

[0045] Preferably, the anomaly correction module comprises:

[0046] An abnormality type identification unit, used for identifying the abnormality type according to the abnormality report;

[0047] A correction strategy generation unit is used to generate a correction strategy according to the exception type. The correction strategy includes reallocating orders, adjusting wave priorities, or increasing delivery resources.

[0048] The dynamic execution unit is used to make real-time adjustments to the wave management plan according to the correction strategy.

[0049] Preferably, the data output module comprises:

[0050] The data recording unit is used to record order details, execution status, inventory changes and distribution resource allocation during the wave execution process to form recorded data;

[0051] A data report generating unit, used for generating a wave execution report according to the recorded data;

[0052] The data interface unit is used to output the wave execution report to an external management system or storage device.

[0053] The above solution of the present invention includes at least the following beneficial effects:

[0054] This system solves the problem of insufficient flexibility of traditional systems through innovative modular design. The order data collection module can obtain all order information including component types, quantities, estimated delivery times and order source information in real time to ensure the timeliness and accuracy of order data. Through close cooperation with the inventory data collection module, the system can grasp inventory dynamics in real time, avoiding the problem of insufficient or excessive inventory, thereby greatly improving the accuracy of inventory management and resource utilization.

[0055] In addition, the order priority determination module in the system performs intelligent priority assessment based on the delivery time, quantity and importance of the order. Through this module, the system can flexibly adjust the order processing sequence when facing sudden changes in orders. For example, when the demand for a key component increases sharply, the system can automatically mark it as a high-priority order to ensure that it is processed first without affecting the execution of other orders. In this way, the system can effectively avoid production delays caused by improper order priority sorting, thereby improving the overall operation efficiency of the production line.

[0056] The wave content generation module combines the type, quantity and priority data of the order to split and reasonably classify the orders into different waves to generate a preliminary wave data set. Through this module, the system can dynamically adjust the composition and order of the waves, avoiding the resource waste and processing bottlenecks caused by the traditional system's reliance on fixed rules to allocate waves. The wave content determination module automatically calculates the resource requirements of each wave by analyzing inventory data and order demand data in real time, and dynamically adjusts order allocation based on inventory data to ensure that each wave can be processed within the appropriate time.

[0057] In addition, the wave priority determination module further optimizes the execution order of waves by combining order priority, inventory matching and distribution resource requirements to ensure that high-priority orders can be processed in a timely manner. The wave scheduling module rationally allocates resources based on wave priority data and distribution resources to ensure the optimal execution order and resource allocation of each wave, avoiding wave execution delays caused by resource conflicts or uneven distribution.

[0058] Most importantly, the system can monitor order data, inventory data, and wave execution status in real time through the anomaly detection module and anomaly correction module, and promptly issue alarms and adjust plans when abnormal situations such as insufficient inventory, order timeouts, or distribution resource shortages occur. Through these mechanisms, the system has a high degree of flexibility and adaptability, can respond to emergencies in a timely manner, and ensure the smooth progress of production and distribution.

[0059] Finally, the data output module can generate wave execution reports in real time, including order details, execution status, inventory changes, and distribution resource allocation for each wave, providing managers with detailed analysis basis to help them make more accurate decisions. This data-driven decision support system not only improves the efficiency and accuracy of order wave management, but also enhances the ability to respond to dynamic demands and emergencies, ultimately improving the operational efficiency and reliability of the entire production and logistics process.

[0060] Compared with existing technologies, this system not only has higher flexibility, but also can quickly adjust and optimize wave management solutions in complex and rapidly changing environments, reducing production and distribution delays, and improving the overall efficiency of the supply chain and customer satisfaction. These innovations and improvements make this system an effective solution to the problems of insufficient flexibility and slow response in traditional wave management systems, with significant technical advantages and broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is an architecture diagram of a component order wave management system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0062] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0063] like Figure 1 As shown, an embodiment of the present invention provides a component order wave management system, the system comprising:

[0064] An order data collection module is used to collect order data in real time, where the order data includes the type, quantity, estimated delivery time and order source information of components;

[0065] The order priority determination module is used to analyze the delivery time, quantity and importance of the order based on the order data, evaluate the priority of each order, and generate order priority data;

[0066] The wave content generation module splits and classifies the orders into corresponding waves according to the order type, quantity and order priority data, and generates the initial wave data set;

[0067] The inventory data collection module is used to obtain the inventory status of components in real time by connecting with various warehouse systems, and to form an inventory data set based on the inventory levels of different components;

[0068] The wave content determination module is used to analyze the demand for orders in each wave and match them with the current inventory data based on the initial wave data set and the inventory data set to obtain matching score data, dynamically adjust the order allocation in the wave based on the matching score data, and generate an optimized wave data set;

[0069] A wave priority determination module is used to determine the wave priority according to the order priority data, the matching score data and the distribution resource requirements, and obtain the wave priority data;

[0070] The wave scheduling module is used to determine the execution order of each wave in the optimized wave data set according to the wave priority data and distribution resources, and dynamically adjust the distribution resource allocation during the wave execution process to form a wave management plan;

[0071] The anomaly detection module monitors order data, inventory data, and wave execution status in real time to identify anomalies that may occur during wave generation or execution, including insufficient inventory, order timeouts, and shortages of distribution resources.

[0072] The abnormality correction module is used to dynamically adjust the wave management plan according to the abnormal situation type;

[0073] The data output module is used to output relevant data during the wave execution process and generate a wave execution report; the relevant data includes order details, execution status, inventory changes and distribution resource allocation for each wave.

[0074] In the embodiment of the present invention, the system manages component orders in waves through a series of modular designs, solving many problems in diversified order processing. The system ensures the integrity and timeliness of orders by collecting order data in real time, including component types, quantities, estimated delivery times, and order source information. The real-time data flow of the order data collection module ensures that the wave management system can respond promptly in a dynamic environment.

[0075] In the order priority determination module, by analyzing the delivery time, quantity and importance of the order, the system can evaluate the priority of each order and generate specific order priority data. This process not only ensures that urgent orders or high-value orders are given priority, but also avoids resource waste and priority confusion. For example, when the order quantity is large and the delivery is urgent, the system can give priority to high-priority orders through the priority algorithm, thereby improving production efficiency and reducing delays.

[0076] The wave content generation module generates the initial wave data set by splitting and classifying the orders into corresponding waves according to the order type, quantity and order priority data. Through this wave splitting and classification, the system can accurately control the order volume of each wave and ensure that the order processing volume within each wave is within a reasonable range, avoiding resource overload or wave execution delay.

[0077] The inventory data collection module connects with each warehouse system to obtain the inventory status of components in real time and form an inventory data set. This module enables the system to grasp inventory changes in real time and avoid order processing delays caused by insufficient inventory. In this way, the system can promptly identify components with inventory shortages and provide accurate data support for subsequent wave adjustments.

[0078] The wave content determination module generates matching score data by analyzing the matching between the demand for orders in each wave and the current inventory data, and dynamically adjusts the order allocation in the wave. This module not only realizes intelligent inventory matching, but also automatically adjusts order allocation according to the actual inventory, avoiding waste of resources and ensuring the optimal allocation of waves.

[0079] The wave priority determination module determines the priority of each wave through order priority data, matching score data and distribution resource requirements, and finally generates wave priority data. The introduction of this module enhances the flexibility of wave management, so that when the order volume fluctuates greatly, the wave priority can be adjusted adaptively to meet the real-time needs of production and distribution.

[0080] The wave scheduling module determines the execution order of waves through analysis of priority data and distribution resources, and dynamically adjusts the allocation of distribution resources according to actual conditions during the execution process. This module ensures that waves can be executed in the optimal order, avoids wave execution conflicts and resource waste, and improves overall distribution efficiency.

[0081] The anomaly detection module monitors order data, inventory data, and wave execution status in real time, and promptly identifies and reports anomalies. By discovering problems such as insufficient inventory, order timeouts, or distribution resource shortages in advance, the system can provide a basis for subsequent anomaly corrections. Based on the identified anomalies, the anomaly correction module dynamically adjusts the wave management plan, optimizes resource allocation in a timely manner, and ensures that the system is always in an efficient operating state.

[0082] Finally, the data output module provides detailed reports during the wave execution process, helping managers track the execution status of orders, inventory changes, and the use of distribution resources. This module provides corporate decision makers with visual execution data for subsequent analysis and optimization. Overall, this system can efficiently and flexibly manage the wave of component orders, improve the automation and refined management level of the production line, and significantly reduce operational risks and costs.

[0083] In a preferred embodiment of the present invention, the order priority determination module includes:

[0084] An order classification unit is used to classify orders into urgent orders and ordinary orders according to the delivery time of the orders, and obtain order classification data;

[0085] An order importance evaluation unit, used to evaluate the importance score of an order based on order source information and order quantity;

[0086] The priority allocation unit is used to calculate the priority score of the order according to the order classification data and the importance score, and generate the order priority data; the calculation formula of the order priority score is: ,in, For the The priority rating of the orders, For the The difference between the delivery deadline of an order and the current time, For the The number of components in an order, For the The importance score of each order, For the The delivery resource demand for each order, , , and is the adjustment coefficient; , For the The source rating of orders, , For the The number of components that need to be delivered in an order, For the The urgency score of the orders, , , and is the weight coefficient; , , and is the weight coefficient.

[0087] In the embodiment of the present invention, the innovation of the order priority determination module is to classify and evaluate orders according to delivery time, quantity and importance. Through the order classification unit, orders can be divided into urgent orders and ordinary orders in real time, which provides an important basis for subsequent priority allocation. Urgent orders have shorter delivery times or higher order quantities, and obviously need to be processed first. By classifying different order types, the system can ensure the optimal allocation of resources and avoid delivery delays and waste of resources caused by incorrect processing order.

[0088] The order importance assessment unit generates an order importance score through a comprehensive assessment based on order source information and quantity. Orders from major customers or long-term cooperative customers will be rated as high priority. This flexible priority setting can ensure the sustainable development of the business and enhance customer satisfaction. At the same time, the consideration of order quantity also helps the system better balance the processing order between large orders and small orders. Larger orders may require more resources due to their large volume, so giving them a higher priority can ensure sufficient resource allocation.

[0089] The priority allocation unit generates order priority data based on order classification data and importance scores. By comprehensively evaluating the urgency and importance of orders and the actual resource requirements of orders, the system can scientifically prioritize orders to ensure the rationality of resource allocation and the efficiency of execution. The optimized priority data provides efficient support for the generation and scheduling of subsequent waves, making order processing more accurate and efficient.

[0090] This priority determination method based on order importance and delivery date significantly improves the automation and intelligence level of the entire order wave management. Whether facing a large number of ordinary orders or sudden emergency orders, the system can respond flexibly, adjust resource allocation in time, and ensure that high-priority orders can be completed quickly and efficiently, thereby improving the company's response speed and customer satisfaction.

[0091] More specifically, Urgency rating of orders It is determined by the order classification unit. Different categories have different values. For example, urgent orders are 1 and ordinary orders are 0.25.

[0092] More specifically, Source ratings for orders By classifying the customers, the values ​​are obtained in the same way as above.

[0093] In a preferred embodiment of the present invention, the wave content generation module includes:

[0094] A preliminary splitting unit, used to divide an order into multiple sub-orders according to order classification data and their corresponding quantities;

[0095] A wave allocation unit is used to allocate sub-orders to different waves according to order priority data to generate an initial wave data set;

[0096] The wave capacity verification unit is used to check whether the total number of orders in each wave exceeds the preset wave capacity threshold, and split the orders that exceed the capacity into other waves.

[0097] In an embodiment of the present invention, the wave content generation module realizes orderly management of orders by splitting orders and allocating them to different waves based on order priority data. Under the action of the preliminary splitting unit, orders are reasonably split into multiple sub-orders according to type and quantity. This process effectively breaks down large orders into small orders suitable for execution, avoiding the situation where resources are over-concentrated or insufficient when processing large orders in a single wave. In addition, the wave allocation unit allocates orders to different waves according to importance and urgency based on the order priority data, which ensures that high-priority orders can be processed first, and low-priority orders can be processed if resources permit.

[0098] The addition of the wave capacity verification unit is a major innovation of this system. It can check in real time whether the total number of orders in each wave exceeds the preset wave capacity threshold to prevent wave overload. If the number of orders in a wave exceeds the capacity limit, the system will redistribute or adjust to ensure that the number of orders in the wave remains within a reasonable range. This preventive verification mechanism effectively avoids resource waste and delivery delays caused by wave overload, and improves the execution efficiency and stability of the system.

[0099] Through wave capacity verification and intelligent wave allocation, the system can optimize the use of resources while processing orders efficiently, ensuring that each wave can complete the task in the shortest time without causing idleness or waste of resources. The implementation of this module makes the management of order waves more refined and scientific, providing a strong guarantee for the efficient operation of the overall system.

[0100] More specifically, the initial split unit includes:

[0101] Input data: Order classification data obtained from the order priority determination module, including urgent orders and ordinary orders. The type, quantity and delivery time of each order.

[0102] Splitting logic: The system analyzes the types and quantities of components in the order and breaks down large orders into smaller orders suitable for execution.

[0103] According to the types of components in the order, it is split into multiple types of sub-orders. For example, an order containing three components A, B, and C will be split into three sub-orders: A component order, B component order, and C component order.

[0104] For larger sub-orders, they will be further split according to the preset maximum order processing volume. For example, if the maximum processing volume for a single delivery is 100 units, the system will split the 500-unit order into 5 sub-orders, each with a processing volume of 100 units.

[0105] Output data: generated sub-order data, including the type and quantity of each sub-order and the ID of the order from which it originated.

[0106] More specifically, the wave allocation unit includes:

[0107] Input data: Sub-order data, from the preliminary split unit. Order priority data, generated by the order priority determination module.

[0108] Allocation logic: The system prioritizes high-priority sub-orders based on order priority data and allocates them to early waves. The allocation of each wave follows the following rules: high-priority orders are allocated first; the total order volume of each wave must not exceed the preset capacity threshold; sub-orders from the same source order are allocated to the same wave as much as possible to reduce scheduling complexity.

[0109] Output data: initial wave data set, including sub-order details in each wave.

[0110] In a preferred embodiment of the present invention, the inventory data collection module includes:

[0111] Data interface unit, used to collect inventory information of various components in real time through communication interfaces with multiple warehouse systems;

[0112] Data integration unit, used to aggregate and unify the format of inventory information to form an inventory data set;

[0113] The data updating unit is used to dynamically update the inventory data set according to the inventory changes collected in real time.

[0114] In the embodiment of the present invention, the core function of the inventory data collection module is to realize the real-time collection of component inventory information through the communication interface with multiple warehouse systems. The data interface unit can effectively connect with multiple warehouse systems to ensure that inventory information is obtained from different warehouses in real time. Through this function, the system can dynamically obtain the inventory data of all warehouses and understand the inventory status in real time, thereby providing a real-time basis for subsequent order processing. The real-time update of inventory information helps to reduce order processing errors caused by lagging inventory data and improve the efficiency of inventory management.

[0115] The data integration unit aggregates and unifies the format of inventory information from different warehouses to generate a standardized inventory data set. Standardization can eliminate the problem of inconsistent data formats in different warehouses and ensure that the system can uniformly process data from various warehouses. The introduction of this module significantly improves the system's adaptability to multi-warehouse environments and ensures the accuracy and consistency of data.

[0116] The data update unit dynamically updates the inventory data set based on the real-time collected inventory changes. Whether it is due to order delivery, inventory replenishment, or other factors of inventory changes, the system can update the inventory data at the first time. This module ensures the timeliness and accuracy of inventory information, allowing the wave management system to adjust the order allocation in the wave in real time, optimize resource scheduling, and avoid delays caused by insufficient inventory.

[0117] Through these functions, the inventory data collection module not only ensures the accuracy and timeliness of inventory data, but also enhances the responsiveness of the wave management system to inventory changes, improving the flexibility and efficiency of the system.

[0118] In a preferred embodiment of the present invention, the wave content determination module includes:

[0119] The matching calculation unit is used to calculate the matching score between the demand quantity of the orders in each wave and the current inventory data according to the initial wave data set, and obtain the matching score data; the calculation formula of the matching score is: ,in, For the The inventory matching score of each wave, For the The number of component types in a wave, For the Wave The order demand for components For the Wave The current inventory of the components, For the The inventory turnover time of each wave, For the The difference between the delivery deadline of the wave and the current time, is the adjustment coefficient;

[0120] A dynamic adjustment unit, used to dynamically adjust the order allocation in the wave according to the matching score data to generate an optimized wave data set, wherein the adjustment content includes removing orders with insufficient inventory or merging them into other waves;

[0121] The verification unit is used to check whether the order allocation results of the optimized wave data set meet the inventory conditions and wave capacity requirements.

[0122] In the embodiment of the present invention, the wave content determination module plays a vital role in the overall system. Its main task is to evaluate the matching degree between the demand for orders in each wave and the current inventory data based on the initially generated wave data set and inventory data set, and dynamically adjust the order allocation in the wave to generate an optimized wave data set.

[0123] First, the matching calculation unit calculates the matching score data based on the matching of the order demand and inventory data in each wave. This process can effectively evaluate the consistency between the orders in each wave and the current inventory. If the order demand in the wave is large and the current inventory cannot meet it, the system will generate a low matching score, indicating that the order allocation needs to be readjusted.

[0124] On this basis, the dynamic adjustment unit dynamically adjusts the order allocation in the wave according to the matching score data. The system will give priority to orders with higher inventory matching scores to ensure that these orders can be processed first in the current wave, while orders with poor inventory matching may be reallocated or merged into other waves. This mechanism avoids delayed delivery due to inventory shortages and improves the efficiency of resource utilization.

[0125] In addition, the verification unit will check the optimized wave data set to ensure that the final order allocation results meet the inventory conditions and wave capacity requirements. The verification process not only ensures the accuracy of inventory matching, but also ensures that the total order volume of each wave is within a reasonable range, avoiding resource overload or uneven allocation. Through verification and adjustment, the system can perform flexible wave management based on actual inventory conditions to ensure the efficiency and accuracy of resource allocation.

[0126] This method of dynamic adjustment of waves based on inventory matching scores not only improves the accuracy of wave allocation, but also ensures timely delivery of orders. In complex and diversified order management, this flexible adjustment and verification mechanism enables the system to adaptively respond to inventory changes, maximizing production efficiency and resource utilization.

[0127] More specifically, the dynamic adjustment unit includes:

[0128] Input data: Initial wave data set, from the wave allocation unit. Inventory matching score data, generated by the matching calculation unit.

[0129] Adjustment logic: The system checks the inventory matching of each sub-order in each wave one by one: if the inventory is insufficient, remove the corresponding sub-order; if the inventory is sufficient, keep the sub-order and calculate its resource requirements. For sub-orders with insufficient inventory, try to merge them into subsequent waves. If the subsequent waves still cannot meet the inventory requirements, they will be marked as "to be replenished".

[0130] Output data: The optimized wave data set, including the order allocation that meets the inventory conditions and the list of pending orders.

[0131] In a preferred embodiment of the present invention, the wave priority determination module includes:

[0132] The data weighting unit is used to perform weighted calculation on each wave according to the order priority data, matching score data and distribution resource requirements to obtain a priority score. The calculation formula for the priority score of a wave is: ,in, For the The priority score of each wave, For the The number of orders in a wave, For the The actual usage of delivery resources for each order. For the The total time window allowed for each wave is , , and is the adjustment coefficient;

[0133] The priority sorting unit is used to sort and generate wave priority data according to the priority scores;

[0134] The adjustment unit is used to readjust the wave priority data when the wave priority ranking changes.

[0135] In the embodiment of the present invention, the wave priority determination module plays a vital role in the entire system. Its main function is to generate wave priority data based on order priority data, matching score data and distribution resource requirements, and adjust the execution order of the waves based on these data.

[0136] First, the data weighting unit performs weighted calculations on each wave based on order priority data, inventory matching score data, and distribution resource requirements to obtain a priority score for each wave. By weighting these factors, the system can ensure that high-priority orders are processed first, while low-priority orders can be arranged in subsequent waves. This comprehensive weighting mechanism ensures that the processing order of waves is consistent with the importance of orders, inventory availability, and actual resource needs.

[0137] The priority sorting unit sorts all waves according to the weighted priority score and generates wave priority data. The generation of wave priorities provides a scientific basis for subsequent wave scheduling, so that the execution order of waves can be flexibly adjusted according to the urgency of the order, inventory matching and resource requirements. This process ensures the timely delivery of high-priority orders and reduces the risk of delays.

[0138] In addition, the adjustment unit is used to readjust the wave priority data when the wave priority ranking changes. When the priority of certain orders changes, such as changes in customer demand, inventory changes, or transportation issues, the adjustment unit can rearrange the execution order of the waves according to the new priority score to ensure that the system can always respond to changes efficiently. Through this mechanism, the system can adjust the priority of waves in real time under dynamically changing order and resource environments, improving the flexibility and responsiveness of wave scheduling.

[0139] This wave priority generation method based on comprehensive weighted scoring ensures the efficiency and accuracy of wave processing, enabling the system to dynamically adapt to changing environments and optimize resource allocation and scheduling order. Through priority sorting and dynamic adjustment, the wave priority determination module provides strong support for subsequent wave scheduling and execution.

[0140] In a preferred embodiment of the present invention, the wave scheduling module includes:

[0141] An execution order determination unit, used for determining the execution order of each wave in the optimized wave data set according to the wave priority data and the distribution resources;

[0142] Resource allocation unit, used to dynamically allocate transport vehicles, delivery personnel and delivery equipment according to the execution requirements of each wave;

[0143] The resource monitoring unit is used to monitor the status of transport vehicles, delivery personnel, and delivery equipment as well as the execution of time windows in real time during the wave execution process, and provide dynamic adjustment suggestions to the resource allocation unit when resource allocation is insufficient or conflicting.

[0144] In the embodiment of the present invention, the role of the wave scheduling module in the entire system is to ensure that the waves can be executed in the optimal order and reasonably allocate distribution resources to achieve efficient wave management and execution. The wave scheduling module not only relies on the wave priority data, but also takes into account the actual distribution resources, and can flexibly adjust the execution order of each wave according to the urgency, priority and availability of resources of the order.

[0145] The execution order determination unit determines the execution order of each wave based on the wave priority data and distribution resources. When determining the execution order, the system gives priority to urgent orders and high-priority orders to ensure that these orders can be processed and delivered as soon as possible. Low-priority orders are scheduled in a later time period to avoid affecting the processing of high-priority orders. This process optimizes the use of resources and avoids resource conflicts and waste.

[0146] The resource allocation unit dynamically allocates transport vehicles, delivery personnel, and other delivery equipment according to the execution requirements of each wave. The system automatically adjusts resource allocation based on factors such as the number of orders in the wave, priority, and delivery urgency to ensure that each wave can be completed smoothly. For example, for urgent orders, the system may allocate more transport vehicles and personnel to ensure on-time delivery; for non-urgent orders, only limited resources may be allocated to optimize overall resource usage.

[0147] The resource monitoring unit monitors the status of transport vehicles, delivery personnel, and delivery equipment as well as the execution of time windows during the wave execution in real time to ensure the effective use of resources. If insufficient resource allocation or resource conflicts are detected, the system can immediately identify the problem and provide dynamic adjustment suggestions to the resource allocation unit. For example, if some resources are occupied or cannot arrive on time, the system will automatically adjust resource allocation and reschedule delivery tasks to ensure that the wave can be completed smoothly as planned.

[0148] Through these mechanisms, the wave scheduling module can dynamically adjust and optimize the execution order and resource allocation of waves according to wave priority, resource status and distribution resources during the actual execution process, thereby improving distribution efficiency, reducing resource waste, and ensuring timely delivery of orders.

[0149] More specifically, the execution order determination unit includes:

[0150] Input data: Wave priority data, generated by the wave priority determination module. Delivery conditions, including vehicle availability, delivery personnel status, delivery equipment, etc.

[0151] Sorting logic: Preliminary sorting of waves is performed based on wave priority data, with waves with higher priorities placed first. Adjustment of sorting results is made based on delivery conditions. For example, if the resource requirements of a wave cannot be met immediately, the execution of the wave is postponed; waves with less resource requirements are executed in advance to improve overall efficiency.

[0152] Output data: optimal execution order list, wave numbers sorted by priority.

[0153] More specifically, the resource allocation unit includes:

[0154] Input data: Optimized wave data set from the dynamic adjustment unit. Distribution resource status, including the availability of vehicles, personnel, and equipment.

[0155] Allocation logic: Calculate the required number of resources based on the order volume and priority of each wave; the system queries the currently available resources in real time and allocates them on demand: high-priority waves are allocated resources first; if resources are insufficient, reduce the resource allocation for low-priority waves or postpone their execution.

[0156] Output data: Resource allocation details for each wave, including vehicle number, distribution personnel allocation and a list of required equipment.

[0157] In a preferred embodiment of the present invention, the anomaly detection module includes:

[0158] Data monitoring unit, used to monitor order data, inventory data and wave execution status in real time;

[0159] An abnormality determination unit, used to determine whether there is an abnormality of insufficient inventory, order timeout or shortage of distribution resources according to a preset abnormality determination threshold;

[0160] The exception reporting unit is used to generate an exception report when an abnormal situation is detected. The exception report includes the exception type and the number of the affected wave.

[0161] In the embodiment of the present invention, the role of the anomaly detection module is to monitor order data, inventory data and wave execution status in real time to ensure that the system can promptly detect and identify possible anomalies during dynamic operation. The system can accurately capture abnormal events such as insufficient inventory, order timeouts or shortage of distribution resources, ensuring that the wave management plan can respond flexibly.

[0162] The data monitoring unit monitors order data, inventory data and wave execution status in real time, providing comprehensive real-time data support for anomaly detection. The unit can monitor the real-time processing status of orders, changes in inventory and the use of distribution resources. Once an anomaly occurs, the system can detect and provide feedback in a timely manner.

[0163] The abnormality judgment unit determines whether there are problems such as insufficient inventory, order timeout, or shortage of distribution resources based on the preset abnormality judgment threshold. Through the threshold setting, the system can automatically identify abnormalities and start the subsequent processing process. For example, when the inventory is insufficient, the system will recognize the shortage of inventory and send an alarm to the abnormality correction module; similarly, if the order exceeds the scheduled delivery time, the system will also trigger abnormality judgment and make timely adjustments.

[0164] When an abnormal situation is detected, the abnormality reporting unit generates an abnormality report, which lists the abnormality type and the affected wave number in detail, helping managers to understand the abnormal situation in time and make decisions. The report also includes possible solutions to provide reference for subsequent corrections. In this way, the abnormality detection module not only improves the system's response speed, but also enhances the system's adaptability to complex scenarios.

[0165] More specifically, the abnormality determination unit includes:

[0166] Input data: order data and inventory data, wave execution status.

[0167] Decision logic: The system checks the following abnormal situations one by one:

[0168] Insufficient inventory: If the order demand for a wave is greater than the current inventory, it will be marked as "Insufficient inventory".

[0169] Order timeout: If the remaining delivery time of an order is lower than a threshold, such as 6 hours, it is marked as "timeout risk".

[0170] Resource shortage: If the current distribution resources cannot meet the wave demand, it will be marked as "resource shortage".

[0171] Output data: exception report, listing the exception type and affected wave number.

[0172] In a preferred embodiment of the present invention, the anomaly correction module includes:

[0173] An abnormality type identification unit, used for identifying the abnormality type according to the abnormality report;

[0174] A correction strategy generation unit is used to generate a correction strategy according to the exception type. The correction strategy includes reallocating orders, adjusting wave priorities, or increasing delivery resources.

[0175] The dynamic execution unit is used to make real-time adjustments to the wave management plan according to the correction strategy.

[0176] In the embodiment of the present invention, the abnormal correction module further improves the flexibility and adaptability of the wave management system by identifying the abnormal type and generating a correction strategy. During the order processing and delivery process, various abnormal situations may occur, such as insufficient inventory, order timeout, resource conflict, etc. The abnormal correction module ensures that the system can be adjusted in time through intelligent processing to avoid affecting normal operation.

[0177] The abnormality type identification unit identifies and classifies the abnormality type based on the abnormality report. Through accurate abnormality classification, the system can identify the root cause of the abnormality and prescribe the right remedy. Whether it is insufficient inventory, delayed orders, or insufficient distribution resources, the system can identify and take corresponding measures in a timely manner.

[0178] The correction strategy generation unit formulates correction strategies based on the type of exception. For different abnormal situations, the system can automatically generate correction plans, such as reallocating orders, adjusting wave priorities, or increasing distribution resources. Through these dynamic adjustment measures, the system can quickly respond to abnormal situations, ensure that wave management is not affected, and maximize the on-time delivery of orders.

[0179] The dynamic execution unit adjusts the wave management plan in real time according to the correction strategy to ensure that the system is always in the optimal operating state. The introduction of this module greatly enhances the system's adaptive ability, enabling it to quickly respond to changes in a complex business environment and reduce production delays and customer complaints.

[0180] More specifically, the revision strategy generation unit includes:

[0181] Input data: exception report, from the exception judgment unit.

[0182] Strategy generation logic:

[0183] If the inventory is insufficient, the following correction plans are provided: remove the affected orders and reallocate them to subsequent waves; prioritize replenishment and arrange fast delivery.

[0184] If an order is overdue, the following correction plans are provided: increase delivery resources to speed up execution; increase the priority of the order and schedule execution in advance.

[0185] If resources are insufficient, the following correction plans are provided: adjust resource allocation to give priority to high-priority waves; postpone the execution time of low-priority waves.

[0186] Output data: Correction plan, listing specific adjustments, including suggestions for resource allocation adjustments, wave sequence changes, or order reallocation.

[0187] In a preferred embodiment of the present invention, the data output module includes:

[0188] The data recording unit is used to record order details, execution status, inventory changes and distribution resource allocation during the wave execution process to form recorded data;

[0189] A data report generating unit, used for generating a wave execution report according to the recorded data;

[0190] The data interface unit is used to output the wave execution report to an external management system or storage device.

[0191] In the embodiment of the present invention, the data output module provides important data support for the subsequent optimization and management of the system by recording and generating wave execution reports. By real-time recording of order details, execution status, inventory changes, and distribution resource allocation during the wave execution process, managers can obtain accurate data feedback and make scientific decisions.

[0192] The data recording unit records all key data in the wave execution process in real time, including order details, execution status, inventory changes, and distribution resource usage of each wave. These data provide the basis for subsequent analysis and optimization. By recording detailed data, the system can track the execution progress of each wave to ensure that no details are missed during the execution process.

[0193] The data report generation unit generates wave execution reports based on the recorded data. The report content includes the execution status of each wave, resource usage, inventory changes, etc., providing managers with a comprehensive execution status view. Through these reports, managers can quickly identify potential problems and make timely adjustments.

[0194] The data interface unit outputs the wave execution report to an external management system or storage device for further analysis and archiving. The design of this module not only improves the transparency of the system, but also enhances the traceability of the data, providing solid data support for subsequent optimization and improvement.

[0195] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A component order wave management system, characterized in that: The system comprises: An order data collection module is used to collect order data in real time, where the order data includes the type, quantity, estimated delivery time and order source information of components; The order priority determination module is used to analyze the delivery time, quantity and importance of the order based on the order data, evaluate the priority of each order, and generate order priority data; The wave content generation module splits and classifies the orders into corresponding waves according to the order type, quantity and order priority data, and generates the initial wave data set; The inventory data collection module is used to obtain the inventory status of components in real time by connecting with various warehouse systems, and to form an inventory data set based on the inventory levels of different components; The wave content determination module is used to analyze the demand for orders in each wave and match them with the current inventory data based on the initial wave data set and the inventory data set to obtain matching score data, dynamically adjust the order allocation in the wave based on the matching score data, and generate an optimized wave data set; A wave priority determination module is used to determine the wave priority according to the order priority data, the matching score data and the distribution resource requirements, and obtain the wave priority data; The wave scheduling module is used to determine the execution order of each wave in the optimized wave data set according to the wave priority data and distribution resources, and dynamically adjust the distribution resource allocation during the wave execution process to form a wave management plan; The anomaly detection module monitors order data, inventory data, and wave execution status in real time to identify anomalies that may occur during wave generation or execution, including insufficient inventory, order timeouts, and shortages of distribution resources. The abnormality correction module is used to dynamically adjust the wave management plan according to the abnormal situation type; The data output module is used to output relevant data during the wave execution process and generate a wave execution report; the relevant data includes order details, execution status, inventory changes and distribution resource allocation for each wave.

2. A component order wave management system according to claim 1, characterized in that: The order priority determination module includes: An order classification unit is used to classify orders into urgent orders and ordinary orders according to the delivery time of the orders, and obtain order classification data; An order importance evaluation unit, used to evaluate the importance score of an order based on order source information and order quantity; The priority allocation unit is used to calculate the priority score of the order according to the order classification data and the importance score, and generate the order priority data; the calculation formula of the order priority score is: ,in, For the The priority rating of the orders, For the The difference between the delivery deadline of an order and the current time, For the The number of components in an order, For the The importance score of each order, For the The delivery resource demand for each order, , , and is the adjustment coefficient; , For the The source rating of orders, , For the The number of components that need to be delivered in an order, For the The urgency score of the orders, , , and is the weight coefficient; , , and is the weight coefficient.

3. A component order wave management system according to claim 2, characterized in that: The wave content generation module includes: A preliminary splitting unit, used to divide an order into multiple sub-orders according to order classification data and their corresponding quantities; A wave allocation unit is used to allocate sub-orders to different waves according to order priority data to generate an initial wave data set; The wave capacity verification unit is used to check whether the total number of orders in each wave exceeds the preset wave capacity threshold, and split the orders that exceed the capacity into other waves.

4. A component order wave management system according to claim 3, characterized in that: The inventory data collection module includes: Data interface unit, used to collect inventory information of various components in real time through communication interfaces with multiple warehouse systems; Data integration unit, used to aggregate and unify the format of inventory information to form an inventory data set; The data updating unit is used to dynamically update the inventory data set according to the inventory changes collected in real time.

5. A component order wave management system according to claim 4, characterized in that: The wave content determination module includes: The matching calculation unit is used to calculate the matching score between the demand quantity of the orders in each wave and the current inventory data according to the initial wave data set, and obtain the matching score data; the calculation formula of the matching score is: ,in, For the The inventory matching score of each wave, For the The number of component types in a wave, For the Wave The order demand for components For the Wave The current inventory of the components, For the The inventory turnover time of each wave, For the The difference between the delivery deadline of the wave and the current time, is the adjustment coefficient; A dynamic adjustment unit, used to dynamically adjust the order allocation in the wave according to the matching score data to generate an optimized wave data set, wherein the adjustment content includes removing orders with insufficient inventory or merging them into other waves; The verification unit is used to check whether the order allocation results of the optimized wave data set meet the inventory conditions and wave capacity requirements.

6. A component order wave management system according to claim 5, characterized in that: The wave priority determination module includes: The data weighting unit is used to perform weighted calculation on each wave according to the order priority data, matching score data and distribution resource requirements to obtain a priority score. The calculation formula for the priority score of a wave is: ,in, For the The priority score of each wave, For the The number of orders in a wave, For the The actual usage of delivery resources for each order. For the The total time window allowed for each wave is , , and is the adjustment coefficient; The priority sorting unit is used to sort and generate wave priority data according to the priority scores; The adjustment unit is used to readjust the wave priority data when the wave priority ranking changes.

7. A component order wave management system according to claim 6, characterized in that: The wave scheduling module includes: An execution order determination unit, used for determining the execution order of each wave in the optimized wave data set according to the wave priority data and the distribution resources; Resource allocation unit, used to dynamically allocate transport vehicles, delivery personnel and delivery equipment according to the execution requirements of each wave; The resource monitoring unit is used to monitor the status of transport vehicles, delivery personnel, and delivery equipment as well as the execution of time windows in real time during the wave execution process, and provide dynamic adjustment suggestions to the resource allocation unit when resource allocation is insufficient or conflicting.

8. A component order wave management system according to claim 7, characterized in that: The anomaly detection module comprises: Data monitoring unit, used to monitor order data, inventory data and wave execution status in real time; An abnormality determination unit, used to determine whether there is an abnormality of insufficient inventory, order timeout or shortage of distribution resources according to a preset abnormality determination threshold; The exception reporting unit is used to generate an exception report when an abnormal situation is detected. The exception report includes the exception type and the number of the affected wave.

9. A component order wave management system according to claim 8, characterized in that: The abnormality correction module comprises: An abnormality type identification unit, used for identifying the abnormality type according to the abnormality report; A correction strategy generation unit is used to generate a correction strategy according to the exception type. The correction strategy includes reallocating orders, adjusting wave priorities, or increasing delivery resources. The dynamic execution unit is used to make real-time adjustments to the wave management plan according to the correction strategy.

10. A component order wave management system according to claim 9, characterized in that: The data output module comprises: The data recording unit is used to record order details, execution status, inventory changes and distribution resource allocation during the wave execution process to form recorded data; A data report generating unit, used for generating a wave execution report according to the recorded data; The data interface unit is used to output the wave execution report to an external management system or storage device.

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