Dynamic overall distribution system and method for mixed flow workshop materials

Abstract

The invention discloses a dynamic overall distribution system and method for mixed flow workshop materials, and relates to the related technical field of material distribution, and the method comprises the steps: interacting workshop basic information, carrying out the information function simplification based on the material distribution, and constructing a digital workshop; carrying out material consumption simulation, determining a line-side minimum safety stock by minimizing the distribution relaxation degree, and determining distribution position groups by the station association degree; a preset delivery time window is pushed forward, and a delivery instruction is generated; determining an initialized delivery strategy in combination with the first delivery material; and transmitting the initialized distribution strategy to a material distribution system, and carrying out dynamic planning regulation and control on material distribution and co-distribution positions. The technical problem that the material distribution efficiency and flexibility are insufficient due to the fact that material supply is difficult to perform timely and accurate material distribution due to frequent switching of product models in a mixed flow production mode in existing material distribution is solved, accurate prediction of material requirements is realized, and the technical effect of improving the material distribution efficiency and flexibility is achieved.

Description

Technical Field

[0001] This application relates to the technical field of material distribution, specifically to a dynamic coordination and distribution system and method for materials in mixed-flow workshops. Background Technology

[0002] In today's highly automated and digitalized industrial production environment, improving production efficiency, reducing operating costs, and ensuring product quality have become core issues of concern for manufacturing enterprises. With the rapid development of intelligent manufacturing technology, intelligent material distribution systems, as an important bridge connecting production processes and material management, are becoming increasingly important. Mixed-flow production, as a flexible and efficient production organization method in modern manufacturing, can flexibly switch between producing different models and specifications of products on the same production line to quickly respond to diversified market demands. However, this production mode also places higher demands on material distribution, requiring both timely and accurate material supply and avoiding inventory backlog to reduce resource waste. However, existing material distribution systems struggle to guarantee timely and accurate material supply and cannot accurately predict material demand, leading to inventory backlog, increased resource waste, and higher operating costs for enterprises. Furthermore, they suffer from unreasonable route planning, low distribution efficiency, and difficulty in quickly and dynamically adjusting to unexpected situations on the production line.

[0003] Therefore, in the current material distribution technologies, there are technical problems such as frequent switching of product models in mixed-flow production modes, which makes it difficult to supply materials in a timely and accurate manner, resulting in insufficient material distribution efficiency and flexibility. Summary of the Invention

[0004] This application provides a dynamic coordination and distribution system and method for materials in mixed-flow workshops, which solves the technical problem of frequent product model switching in mixed-flow production modes, which makes it difficult to supply materials in a timely and accurate manner, resulting in insufficient material distribution efficiency and flexibility. It enables accurate prediction of material demand and achieves the technical effect of improving material distribution efficiency and flexibility.

[0005] This application provides a dynamic coordination and distribution system for materials in a mixed-flow workshop. The system includes: a digital workshop construction module, which interacts with basic workshop information and simplifies information functionality based on material distribution to construct a digital workshop. The basic workshop information includes a production mode, specifically a mixed-flow production mode. A distribution location grouping determination module is used to perform material consumption simulation based on the digital workshop, determine the minimum safety stock at the line edge by minimizing distribution slack, and determine distribution location groups based on workstation correlation. The minimum safety stock at the line edge is identified by a line edge inventory location code. The system includes: an instruction generation module, which generates delivery instructions based on the minimum safety stock and a preset delivery time window, and determines the first delivery material based on the delivery location grouping; an initialization delivery strategy determination module, which receives the delivery instructions and determines an initialization delivery strategy based on the first delivery material, wherein the initialization delivery strategy prioritizes the primary delivery location; and a material dynamic planning and control module, which transmits the initialization delivery strategy to the material delivery system for dynamic planning and control of material delivery and co-delivery locations.

[0006] In a possible implementation, the delivery location grouping determination module further performs the following processing: calling historical production line data, verifying and determining the initial inventory distribution, and determining the first relaxation metric level; based on the initial inventory distribution, and constrained by the delivery time limit based on the material warehouse, adjusting the inventory quantity to determine the optimized inventory distribution, and determining the second relaxation metric level; performing iterative adjustments until a preset number of iterations is met, verifying the first relaxation metric level and the second relaxation metric level, and selecting the inventory distribution with the smallest relaxation metric level as the minimum safety stock at the line edge.

[0007] In a possible implementation, the delivery location grouping determination module further performs the following processing: preset the inventory quantity shrinkage step size; traverse the initial inventory distribution, randomly select the line-side inventory location of the production line, adjust it based on the inventory quantity shrinkage step size, and determine the adjusted inventory distribution; combine the digital workshop to perform global simulation and qualification analysis on the adjusted inventory distribution, and screen and optimize the inventory distribution.

[0008] In a possible implementation, the delivery instruction generation module further performs the following processing: receiving the delivery instruction and determining the primary delivery location; determining the co-delivery location based on the delivery capacity and the grouping of delivery locations; allocating the primary delivery location and the co-delivery location by delivery ratio and determining the first delivery material.

[0009] In a possible implementation, the material dynamic planning and control module further performs the following processing: identifying the initial delivery strategy and determining the first delivery strategy for the main delivery location; executing the first delivery strategy, traversing the co-delivery locations, and determining the second priority based on the dynamic update of the delivery time window; determining the second priority and the second delivery strategy, performing position dynamic planning as the delivery process progresses, and completing the delivery of the first delivery material.

[0010] In a possible implementation, the material dynamic planning and control module further performs the following processing: the delivery time window is the time interval between the starting node of the delivery location and the node of the minimum safety stock, and the delivery time window is a dynamic window; the material consumption status of the co-delivery location is interacted with to determine the window bias based on the delivery time window; if the window bias is greater than a preset bias, a strong constraint is applied to the dynamic sorting; if the window bias is less than or equal to the preset bias, a weak constraint is applied to the dynamic sorting.

[0011] In a possible implementation, the dynamic coordination and distribution system for materials in mixed-flow workshops also performs the following processing: if it is a concurrent distribution task, it performs distribution collision analysis to locate the distribution collision point; it traverses the distribution collision point and determines the avoidance strategy by using the dynamic sorting adjustment of the co-distribution location and the adjustment of the distribution speed as the avoidance method; and performs dynamic adjustment and compensation of material distribution based on the avoidance strategy.

[0012] This application also provides a dynamic coordination and distribution method for materials in a mixed-flow workshop. The method includes: interacting with basic workshop information, simplifying information functionality based on material distribution, and constructing a digital workshop, wherein the basic workshop information includes a production mode, and the production mode is a mixed-flow production mode; based on the digital workshop, performing material consumption simulation, determining the minimum safety stock at the line edge by minimizing distribution slack, and determining the distribution location grouping by workstation correlation, wherein the minimum safety stock at the line edge is identified by a line edge inventory location code; based on the minimum safety stock, advancing a preset distribution time window, generating a distribution instruction, and determining the first distribution material based on the distribution location grouping based on the distribution capacity; receiving the distribution instruction, and determining an initial distribution strategy based on the first distribution material, wherein the initial distribution strategy prioritizes the main distribution location; and transmitting the initial distribution strategy to the material distribution system for dynamic planning and control of material distribution and cooperative distribution locations.

[0013] This application proposes a dynamic coordination and distribution system and method for materials in mixed-flow workshops. This system facilitates the exchange of basic workshop information, simplifies information functionality based on material distribution, and constructs a digital workshop. Material consumption simulation is performed to determine the minimum safety stock at the line edge by minimizing distribution slack, and distribution location grouping is determined based on workstation correlation. A preset distribution time window is advanced to generate distribution instructions. An initial distribution strategy is determined based on the first delivered material. This initial distribution strategy is then transmitted to the material distribution system for dynamic planning and control of material distribution and coordinated distribution locations. This addresses the technical problem of frequent product model switching in mixed-flow production modes, which leads to difficulties in timely and accurate material supply, resulting in insufficient material distribution efficiency and flexibility. The system achieves accurate prediction of material demand, thereby improving the efficiency and flexibility of material distribution. Attached Figure Description

[0014] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments of this disclosure will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0015] Figure 1 A schematic diagram of the structure of a dynamic overall distribution system for materials in a mixed-flow workshop provided in an embodiment of this application; Figure 2 This is a flowchart illustrating a dynamic coordination and distribution method for materials in a mixed-flow workshop, as provided in an embodiment of this application.

[0016] Explanation of reference numerals in the attached diagram: Digital workshop construction module 10, delivery location grouping determination module 20, delivery instruction generation module 30, initial delivery strategy determination module 40, and material dynamic planning and control module 50. Detailed Implementation

[0017] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below.

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application will be provided in conjunction with the accompanying drawings. The described embodiments should not be considered as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] In the following description, references to "some embodiments" describe a subset of all possible embodiments. However, it is understood that "some embodiments" may be the same or different subsets of all possible embodiments and may be combined with each other without conflict. The terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.

[0020] This application provides a dynamic coordination and distribution system for materials in mixed-flow workshops, such as... Figure 1 As shown, the system includes: The digital workshop construction module 10 is used to interact with basic workshop information, simplifying information functionality based on material distribution to construct a digital workshop. The basic workshop information includes a production mode, specifically a mixed-model production mode. Mixed-model production (MMP) is a flexible production method where multiple products of different models, specifications, or configurations are produced simultaneously or sequentially on the same production line according to market demand or production plans. Specific characteristics of mixed-model production include multi-product co-production, unlike single-product mass production. Mixed-model production requires a high degree of flexibility and adjustability of the production line; rapid changeover, where equipment, tooling, and fixtures on the production line need to be quickly adjusted or replaced to achieve rapid switching between different products, reducing changeover time and costs; and, due to the simultaneous or alternating production of multiple products on the production line, extremely high requirements are placed on the accuracy and timeliness of material distribution, necessitating the establishment of an efficient material management system to ensure that the correct type and quantity of materials are delivered to the correct workstation at the correct time. Basic workshop information includes information on all aspects of the production workshop, including but not limited to production equipment, processes, product types, production modes, material types, inventory levels, and production plans. Interactive workshop basic information refers to a comprehensive understanding of the workshop's operational status. Information simplification based on material distribution means filtering out key information directly related to material distribution from the basic workshop information, such as material consumption rates, inventory status, material demand planning, and on-line flow. Only material consumption data is retained, including the consumption rate and cycle time of each material, to accurately predict and plan material demand. Attention is paid to the flow of materials on the production line, including flow speed, flow path, and bottleneck stations, to optimize material distribution strategies. Information irrelevant or minimally impactful to material distribution, such as information from non-critical equipment, is removed. The system first identifies operational status and non-critical process parameters to reduce data processing volume and improve decision-making efficiency. Then, based on the filtered and simplified information, a digital model of the workshop is built using simulation software. This model rationally arranges equipment, workbenches, and material storage areas. It can reflect the workshop's operational status in real time, including material consumption, inventory status, and production progress. The digital workshop includes a material management system, a production monitoring system, and a production scheduling system. The material management system implements dynamic inventory management, updates material inventory levels in real time to avoid backlogs and shortages, and uses algorithms to optimize material delivery routes and timing to ensure continuous supply to the production line. The production monitoring system collects data during the production process through IoT devices to monitor process status and efficiency. The production scheduling system automatically adjusts production plans based on real-time data and production demand to improve resource utilization.

[0021] The delivery location grouping determination module 20 is used to perform material consumption simulation based on the digital workshop, determine the minimum safety stock at the line edge by minimizing the delivery slack, and determine the delivery location grouping by the workstation correlation. The minimum safety stock at the line edge is identified by the line edge inventory location code. Material consumption simulation refers to using digital technology to simulate and predict the consumption process of materials in a workshop. Through simulation, it helps understand material consumption at different points in time and identify potential shortages or surpluses, ensuring timely and accurate material supply and preventing production interruptions and waste. Delivery slack refers to the difference between the time it takes for materials to arrive at the production line and the time it takes for them to be used. A smaller difference indicates a better delivery cycle, meaning materials arrive at the production line and are used more promptly. Specifically, historical data is collected and analyzed to understand the actual situation and problems in material delivery. Based on a digital workshop, simulation software is used to simulate the material delivery process, considering different delivery strategies and solutions. Through simulation results, the optimal delivery strategy and solution that minimizes delivery slack is found, such as adjusting delivery frequency and optimizing delivery routes. This leads to the determination of the minimum safety stock at the production line. The minimum safety stock at the production line refers to the inventory level that needs to be delivered promptly before the material quantity at the production line reaches a certain minimum level, ensuring that the production line is not interrupted due to material shortages. Specifically, it considers the production line's... Multiple factors, such as production rate, material consumption rate, delivery cycle, and material quality stability, are considered in material consumption simulation. This simulation assesses production conditions under different inventory levels to find the minimum safety stock that meets production needs while reducing inventory costs. As production conditions change (e.g., order volume increases or decreases, production rate changes), the minimum safety stock level needs to be checked and adjusted periodically. Workstation correlation refers to the degree of interrelationship between different workstations in terms of material requirements and production processes. Detailed analysis of the production line reveals the material demand relationships and production process sequences between different workstations. Based on workstation correlation, adjacent or related workstations are grouped into the same delivery location group. Reasonable delivery location grouping reduces overlapping and duplication of delivery paths, improves delivery efficiency, and lowers logistics costs. The minimum safety stock identifier is an information identifier used to identify and record the location and minimum safety stock level of the line-side inventory. This identifier typically includes the line-side inventory location code, material name, specifications, and minimum safety stock level, helping workshop managers understand inventory status in real time and promptly distribute and replenish materials. By using digital technology to accurately simulate and predict the material distribution process, we can achieve timely and accurate material supply, reduce inventory costs, and improve production efficiency.

[0022] The delivery instruction generation module 30 is used to generate delivery instructions based on the minimum safety stock and a preset delivery time window, and to determine the first delivery material based on the delivery location grouping. Based on minimum safety stock, the generation of delivery instructions by pushing forward a preset delivery time window specifically refers to the real-time monitoring of the material quantity in the line-side inventory and comparing it with the preset minimum safety stock quantity. When the inventory quantity drops to or falls below the minimum safety stock, an early warning signal is issued and the delivery process is triggered. Taking into account the material delivery cycle (including order processing time, transportation time, etc.), a preset delivery time window is pushed forward based on the delivery cycle and the current inventory status. That is, delivery instructions must be issued within this time window to ensure that materials can reach the production line when needed. Based on these automatically generated delivery instructions, detailed information such as the type and quantity of the delivered materials, the delivery destination (i.e., the specific delivery location group), and the delivery time is typically included. Combined with the delivery location group, the first delivery material is determined based on the delivery capacity. Specifically, in each delivery location group, the type and quantity of the first delivery material are determined according to the delivery capacity (i.e., the amount of material that can be carried in each delivery) and the priority of material demand (such as urgency, waiting time of upstream processes on the production line, etc.). The first delivery material can be delivered to the production line first to meet the urgent needs of the production line or maintain the continuous operation of the production line.

[0023] An initialization delivery strategy determination module 40 receives the delivery instructions and, in conjunction with the first delivery material, determines an initialization delivery strategy, prioritizing the main delivery location. Upon receiving the delivery instructions, the digital workshop parses the information within them, including the type and quantity of the delivered materials, delivery location grouping, and delivery time requirements. This information, combined with the first delivery material (materials urgently needed on the production line or those with the greatest impact on the production process), and considering current production demands, material inventory, and delivery location grouping information, determines the initialization delivery strategy. In this process, the main delivery location is prioritized, meaning its delivery needs are met first. Specifically, this is achieved by optimizing delivery routes, adjusting delivery sequences, or increasing delivery frequency to ensure the first delivery material is delivered to the main delivery location first. The inventory at the main delivery location is monitored in real time; if the inventory falls below the safety stock level, a replenishment mechanism is immediately triggered to ensure continuous material supply. The delivery strategy is flexibly adjusted based on the actual production line conditions and changes in material demand. For example, in an emergency, the frequency of deliveries to the main distribution point can be temporarily increased or the types and quantities of delivered materials can be adjusted. The main distribution point corresponds to the workstation on the production line that receives the most critical or urgently needed materials, and its delivery needs have a higher urgency. The main distribution point is often closely connected to other key links in the supply chain. Prioritizing its delivery needs helps maintain the smoothness and coordination of the supply chain. Prioritizing the needs of the main distribution point can often bring greater production efficiency and cost savings. Material shortages at the main distribution point may cause the entire production line to stagnate or slow down, resulting in greater losses.

[0024] The material dynamic planning and control module 50 is used to transmit the initial delivery strategy to the material delivery system for dynamic planning and control of material delivery and co-delivery locations. The material delivery system is typically a comprehensive management system integrating order processing, inventory management, delivery route planning, and vehicle scheduling. Specifically, the material delivery system monitors the material consumption of the production line in real time, including information such as inventory levels and material consumption rates at each delivery location, and then makes dynamic adjustments, including delivery route optimization, delivery volume adjustment, and delivery sequence adjustment. Delivery route optimization refers to dynamically adjusting the delivery route based on real-time production conditions, the location and priority of delivery locations, etc., to reduce delivery time and costs. Cost and delivery volume adjustment refers to dynamically adjusting the amount of materials delivered each time based on the actual needs and inventory status of each delivery location to avoid inventory backlog or shortage. Delivery sequence adjustment refers to the real-time adjustment of the delivery sequence in case of emergencies or unexpected events (such as a sudden increase in demand at a certain delivery location) to prioritize meeting urgent needs. When delivering materials to the main delivery location, a small amount of materials is also delivered to the auxiliary delivery locations (other delivery locations on the production line besides the main delivery location) to ensure a balance of material supply among the delivery locations. The material delivery plan is also dynamically adjusted based on real-time data from the delivery process.

[0025] The dynamic coordination and distribution system for mixed-flow workshop materials according to embodiments of the present invention addresses the technical problem of frequent product model switching in mixed-flow production modes, which leads to difficulties in timely and accurate material supply, resulting in insufficient material distribution efficiency and flexibility. The system achieves accurate prediction of material demand, thereby improving the efficiency and flexibility of material distribution. The dynamic coordination and distribution system for mixed-flow workshop materials includes: a digital workshop construction module 10, a distribution location grouping determination module 20, a distribution instruction generation module 30, an initialization distribution strategy determination module 40, and a material dynamic planning and control module 50.

[0026] The specific configuration of the delivery location grouping determination module 20 will be described in detail below. The delivery location grouping determination module 20 may further include: calling historical production line data, verifying and determining the initial inventory distribution, and determining the first relaxation metric level. Historical production line data, including inventory data and production records, is collected from the production management system, inventory management system, etc. Then, based on the historical production line data, the current inventory distribution is verified and adjusted to ensure its rationality and accuracy. The initial inventory distribution refers to the allocation of inventory in different storage locations (such as warehouses, production line edges, etc.). Finally, using an algorithm (such as the relaxation iteration method), based on the initial inventory distribution and preset constraints (such as delivery time limits, production costs, etc.), the first relaxation metric level is calculated. The smaller the relaxation metric level, the more flexible and secure the inventory distribution, and the better it meets production needs. This is used to evaluate the flexibility and security of the inventory distribution. Specifically, preset constraints (delivery time limits, production costs, demand fluctuations, etc.) are used to construct an optimization objective function: ; in, This represents the total cost, including production and distribution costs. This represents the specific cost function for each node (or production line). This represents the relaxation factor, which controls the degree of relaxation of the constraints. Indicates the first A constraint function, Indicates the first Each constraint has an allowable boundary or threshold. The inventory distribution is iteratively adjusted using a relaxation iteration method to maximize or minimize a certain objective function while satisfying all preset constraints. Finally, a relaxation metric, the first relaxation metric, is calculated, which is considered the minimum relaxation factor required to initially satisfy the main constraints. Assess the flexibility and safety margin of the current inventory distribution.

[0027] It also includes adjusting inventory levels based on the initial inventory distribution, constrained by the delivery time limit of the material warehouse, to determine an optimized inventory distribution, and determining a second relaxation metric. The delivery time limit of the material warehouse refers to the time limit for delivery from the material warehouse to the production line. Based on the initial inventory distribution, the inventory level is adjusted with the delivery time limit as a constraint to ensure that the material supply on the production line can meet production needs in a timely manner. Specifically, by adjusting the inventory level, the inventory distribution is made more reasonable and efficient, thereby determining an optimized inventory distribution, that is, while meeting production needs, reducing inventory costs and increasing inventory turnover. Then, the relaxation metric is calculated to obtain the second relaxation metric, and the effect of inventory distribution optimization is evaluated.

[0028] This also includes iterative adjustments until a preset number of iterations is met, calibrating the first relaxation metric and the second relaxation metric, and selecting the inventory distribution with the smallest relaxation metric as the minimum safety stock at the line edge. The inventory distribution is iteratively adjusted multiple times, each iteration based on the previous optimization result and new constraints, until the preset number of iterations is reached. After the iterations are completed, all relaxation metrics are calibrated and compared, and the inventory distribution with the smallest relaxation metric is selected as the final optimization result. This inventory distribution is the minimum safety stock at the line edge, which ensures both inventory safety and flexibility while meeting production needs.

[0029] The following will describe the specific configuration of the delivery location grouping determination module 20 in detail. The delivery location grouping determination module 20 may further include: a preset inventory reduction step size. The preset inventory reduction step size refers to a pre-set step size or magnitude for reducing inventory before adjusting the inventory distribution, based on historical data, production demand, supply chain stability, etc. This is used to control the precision and magnitude of inventory adjustments, ensuring that the adjustment process gradually approaches the optimal inventory distribution without causing production interruptions or other adverse effects due to excessive adjustment magnitude. It also includes traversing the initial inventory distribution, randomly selecting production line-side inventory locations, and adjusting them based on the preset inventory reduction step size to determine the adjusted inventory distribution. The process involves traversing the initial inventory distribution (information on inventory quantity, type, status, etc., of various warehouses, production line-side, and other storage locations), randomly selecting one production line-side inventory location from multiple locations as the adjustment target, and adjusting the inventory quantity for the selected location according to the preset inventory reduction step size, for example, reducing the inventory quantity.

[0030] This also includes conducting a global simulation and compliance analysis of the adjusted inventory distribution in conjunction with the digital workshop, and selecting and optimizing the inventory distribution. Specifically, the global simulation covers all production line-edge inventory points to ensure that each point can meet continuous production needs. Through simulation, the impact of different inventory distribution schemes on production efficiency and costs can be predicted and evaluated. During the global simulation process, the compliance of the inventory distribution is analyzed, including whether the inventory level is sufficient to meet production needs and whether the inventory distribution is reasonable to reduce inventory costs and improve inventory turnover. Based on the results of the global simulation and compliance analysis, the optimal inventory distribution scheme is selected based on factors such as lowest production cost, highest production efficiency, and fastest inventory turnover.

[0031] The specific configuration of the delivery instruction generation module 30 will be described in detail below. The delivery instruction generation module 30 may further include: receiving the delivery instruction and determining the primary delivery location. This involves receiving a delivery instruction containing information about the materials to be delivered, the delivery address, and the delivery time, and determining the primary delivery location based on the material type, quantity, delivery address, and other information in the delivery instruction, as well as factors such as the inventory status and delivery capacity of the primary delivery location. It also includes determining co-delivery locations based on the delivery capacity and the delivery location grouping. The delivery capacity refers to the maximum amount of material that each delivery node can carry in a single delivery process. Based on the delivery capacity and delivery location grouping, i.e., based on delivery distance, delivery time, traffic conditions, and material type, the most suitable co-delivery location is selected to assist in completing the delivery task. The co-delivery location, in this case, refers to other delivery nodes besides the primary delivery location that are used to complete a specific delivery task. Finally, it includes allocating the primary delivery location and the co-delivery location by delivery ratio to determine the first delivery material. Delivery ratio allocation refers to allocating the total delivery volume according to a certain ratio based on factors such as the delivery capacity, material types, and customer needs of the primary and secondary delivery locations. This ensures the smooth completion of delivery tasks while optimizing delivery costs, improving delivery efficiency, and enhancing service levels. First-delivery materials refer to materials selected first from all materials requiring delivery, based on certain standards or conditions. This ensures the timely delivery of critical or high-priority materials to meet customers' urgent needs.

[0032] The specific configuration of the material dynamic planning and control module 50 will be described in detail below. The material dynamic planning and control module 50 may further include: identifying the initial delivery strategy and determining the first delivery strategy for the main delivery location. Identifying the initial delivery strategy refers to identifying and obtaining the delivery route planning, delivery time estimation, and delivery resource allocation. After determining the main delivery location, a detailed delivery plan and strategy are formulated, including specific delivery routes, delivery order, delivery volume, and delivery time, to ensure that the main delivery location can efficiently and accurately complete its delivery tasks. It also includes executing the first delivery strategy, traversing the co-delivery locations, and determining a second priority based on the dynamic update of the delivery time window. Delivery tasks are executed according to the first delivery strategy of the main delivery location. During execution, the delivery capacity and delivery demand of the co-delivery locations are considered. Based on the dynamic update of the delivery time window (such as production line emergencies, changes in customer demand, etc.), specifically, the second priority is determined according to the delivery capacity, location, current task progress, and the update status of the delivery time window of the co-delivery locations, guiding which co-delivery locations should prioritize the execution of subsequent delivery tasks. It also includes a second delivery strategy that determines the second priority, dynamically plans the delivery order as the delivery progresses, and completes the delivery of the first delivery material. Based on the second priority, a second delivery strategy is formulated for the co-delivery location, including how to allocate delivery tasks, plan delivery routes, and arrange delivery times. During the execution of delivery tasks, due to various unforeseen factors (such as equipment failure, changes in customer needs, etc.), the delivery process may change. Therefore, the system monitors these changes in real time and dynamically plans the delivery order according to the new situation, including reallocating delivery tasks, adjusting delivery routes, and modifying delivery times, ultimately completing the delivery task of the first delivery material.

[0033] The specific configuration of the material dynamic planning and control module 50 will be described in detail below. The material dynamic planning and control module 50 may further include: the delivery time window being the time interval between the starting node of the delivery location and the node of the minimum safety stock, and the delivery time window being a dynamic window. The delivery time window refers to the time period required from the start of delivery of a material from the delivery location (such as a warehouse or distribution center) to the material reaching its corresponding minimum safety stock node. This time window considers various factors such as transportation time, traffic conditions, and possible delays, and is dynamically changing. It also includes interacting with the material consumption status of the co-delivery location to determine the window bias based on the delivery time window. Material consumption status refers to the consumption of materials at the co-delivery stations (i.e., nodes that assist the main delivery station in delivery), including current inventory levels, consumption rates, and projected future consumption. Specifically, communication is established with the delivery stations to obtain accurate material consumption status information. Due to the volatility of material consumption during actual production line operation, the delivery time window also needs to be dynamically adjusted accordingly. Window bias refers to the degree of deviation between the current delivery progress and the delivery time window. Specifically, it is calculated by comparing the actual material consumption rate, remaining inventory level, and the expected arrival time within the time window. If the actual consumption rate is faster than expected, or the remaining inventory level is lower than the safety level, the window bias will increase, indicating that the delivery task may face time pressure. Then, the order of co-delivery stations is dynamically adjusted based on the window bias. Furthermore, if the window bias is greater than a preset bias, a strong constraint is applied to the dynamic ordering. If the window offset is greater than the preset offset, it indicates that the material consumption rate at some co-delivery locations is exceeding expectations, or that the remaining inventory is insufficient to support the next delivery cycle. In this case, strong constraints need to be applied to the dynamic sequencing, meaning that delivery tasks must be executed more strictly according to the established delivery order and schedule to reduce further delays and avoid production interruptions. Alternatively, if the window offset is less than or equal to the preset offset, weak constraints can be applied to the dynamic sequencing. If the window offset is less than or equal to the preset offset, it indicates that the material consumption status of these co-delivery locations is relatively stable, allowing for weaker constraints on the dynamic sequencing. This means adopting a more flexible delivery strategy, such as fine-tuning the delivery order and schedule based on real-time material consumption to improve material delivery efficiency.

[0034] The following will describe in detail the specific configuration of the dynamic coordination and distribution system for materials in mixed-flow workshops. The dynamic coordination and distribution system for materials in mixed-flow workshops further includes: for concurrent delivery tasks, performing delivery collision analysis to locate delivery collision points. If material delivery is a concurrent delivery task, delivery collision analysis is performed using algorithms and data analysis methods. Specifically, the spatiotemporal distribution of delivery tasks, vehicle route planning, and delivery time are comprehensively simulated and predicted to identify potential collision risk points, i.e., delivery collision points. These refer to the specific locations where two or more delivery tasks may meet and cause conflict or collision during the delivery process, and these predicted delivery collision points are located. The system also includes traversing the delivery collision points and determining avoidance strategies using dynamic sorting adjustments of co-delivery locations and delivery speed adjustments as avoidance methods. All identified delivery collision points are traversed, and the risk level and impact range of each collision point are assessed. Then, a dynamic sorting and adjustment of delivery locations and delivery speed are used as avoidance methods. Specifically, based on the risk level of the collision point and the priority of the delivery tasks, the execution order of delivery tasks is dynamically adjusted. For example, through algorithm optimization, delivery routes and schedules are replanned to ensure that high-risk collision points are prioritized or avoided; when approaching a collision point, delivery speed is adjusted to avoid collisions. The system also includes dynamic adjustment and compensation of material delivery based on the avoidance strategy. After the avoidance strategy is implemented, delivery tasks are adjusted in real time to ensure the smooth execution of the overall delivery plan, including reallocating delivery resources, adjusting delivery time windows, and optimizing delivery routes.

[0035] In the above text, refer to Figure 1 A dynamic coordination and distribution system for materials in a mixed-flow workshop, according to an embodiment of the present invention, is described in detail. Next, reference will be made to... Figure 2 A dynamic and coordinated distribution method for materials in a mixed-flow workshop is described according to an embodiment of the present invention.

[0036] Dynamic and coordinated distribution methods for materials in mixed-flow workshops, such as Figure 2As shown, the method includes: exchanging basic workshop information, simplifying information functionality based on material distribution, and constructing a digital workshop, wherein the basic workshop information includes a production mode, and the production mode is a mixed-flow production mode; based on the digital workshop, performing material consumption simulation, determining the minimum safety stock at the line edge by minimizing distribution slack, and determining the distribution position grouping by workstation correlation, wherein the minimum safety stock at the line edge is identified by a line edge inventory location code; based on the minimum safety stock, advancing a preset distribution time window, generating a distribution instruction, and determining the first distribution material based on the distribution position grouping based on the distribution capacity; receiving the distribution instruction, and determining an initial distribution strategy based on the first distribution material, wherein the initial distribution strategy prioritizes the main distribution position; transmitting the initial distribution strategy to the material distribution system for dynamic planning and control of material distribution and cooperative distribution positions.

[0037] In one possible implementation, determining the minimum safety stock at the production line edge by minimizing delivery slack includes: calling historical production line data, verifying and determining the initial inventory distribution, and determining a first slack metric; based on the initial inventory distribution, adjusting the inventory quantity to determine an optimized inventory distribution with the delivery time limit based on the material warehouse as a constraint, and determining a second slack metric; performing iterative adjustments until a preset number of iterations is met, verifying the first slack metric and the second slack metric, and selecting the inventory distribution with the smallest slack metric as the minimum safety stock at the production line edge.

[0038] In one possible implementation, the dynamic coordination and distribution method for materials in a mixed-flow workshop includes: presetting an inventory reduction step size; traversing the initial inventory distribution, randomly selecting the line-side inventory location of the production line, adjusting it based on the inventory reduction step size, and determining the adjusted inventory distribution; and combining the digital workshop to perform global simulation and qualification analysis on the adjusted inventory distribution, and screening and optimizing the inventory distribution.

[0039] In one possible implementation, determining the first delivery material based on the delivery capacity includes: receiving the delivery instruction and determining the primary delivery location; determining the cooperative delivery location based on the delivery capacity and the grouping of the delivery locations; allocating the primary delivery location and the cooperative delivery location by delivery ratio to determine the first delivery material.

[0040] In one possible implementation, the dynamic planning and control of material delivery and co-delivery locations includes: identifying the initial delivery strategy and determining a first delivery strategy for the main delivery location; executing the first delivery strategy, traversing co-delivery locations, and determining a second priority based on the dynamic update of the delivery time window; determining a second delivery strategy for the second priority, and performing dynamic planning of the location as the delivery process progresses to complete the delivery of the first delivery material.

[0041] In one possible implementation, the dynamic planning of the order during the delivery process includes: the delivery time window being the time interval between the starting node of the delivery position and the node of the minimum safety stock, and the delivery time window being a dynamic window; interacting with the material consumption status of the co-delivery position to determine a window bias based on the delivery time window; if the window bias is greater than a preset bias, applying strong constraints to the dynamic sorting; if the window bias is less than or equal to the preset bias, applying weak constraints to the dynamic sorting.

[0042] In one possible implementation, the dynamic coordination and distribution method for materials in a mixed-flow workshop further includes: if it is a concurrent distribution task, performing distribution collision analysis to locate the distribution collision point; traversing the distribution collision point and determining an avoidance strategy by using dynamic sorting adjustment of the co-distribution location and adjustment of the distribution speed as an avoidance method; and performing dynamic adjustment and compensation of material distribution based on the avoidance strategy.

[0043] The dynamic coordination and distribution system for mixed-flow workshop materials provided in this embodiment of the invention can execute the dynamic coordination and distribution method for mixed-flow workshop materials provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0044] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0045] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A dynamic overall planning and distribution system for materials in a mixed-flow workshop, characterized in that, The system includes: A digital workshop construction module is used to interact with basic workshop information, simplify information functionality based on material distribution, and construct a digital workshop. The basic workshop information includes a production mode, which is a mixed-flow production mode. The delivery location grouping determination module is used to perform material consumption simulation based on the digital workshop, determine the minimum safety stock at the line edge by minimizing the delivery slack, and determine the delivery location grouping by the workstation correlation. The minimum safety stock at the line edge is identified by the line edge inventory location code. The delivery instruction generation module is used to generate delivery instructions based on the minimum safety stock and a preset delivery time window, and to determine the first delivery material based on the delivery location grouping. An initial delivery strategy determination module is used to receive the delivery instruction and, in conjunction with the first delivery material, determine an initial delivery strategy, wherein the initial delivery strategy prioritizes the primary delivery location. The material dynamic planning and control module is used to transmit the initial delivery strategy to the material delivery system and perform dynamic planning and control of material delivery and cooperative delivery locations.

2. The dynamic overall distribution system for materials in a mixed-flow workshop as described in claim 1, characterized in that, The method of determining the minimum safety stock at the line edge by minimizing distribution slack includes: Call historical production line data, verify and determine the initial inventory distribution, and determine the first relaxation metric level; Based on the initial inventory distribution, and constrained by the delivery time limit based on the material warehouse, the inventory quantity is adjusted to determine the optimized inventory distribution, and the second relaxation metric level is determined. Perform iterative adjustments until the preset number of iterations is met, calibrate the first relaxation metric and the second relaxation metric, and select the inventory distribution with the smallest relaxation metric as the minimum safety stock at the line edge.

3. The dynamic coordination and distribution system for materials in a mixed-flow workshop as described in claim 2, characterized in that, The system also includes: Preset inventory reduction step size; Traverse the initial inventory distribution, randomly select the lineside inventory location of the production line, and adjust it based on the inventory shrinkage step size to determine the adjusted inventory distribution; Based on the digital workshop, a global simulation and qualification analysis are performed on the adjusted inventory distribution to screen and optimize the inventory distribution.

4. The dynamic coordination and distribution system for materials in a mixed-flow workshop as described in claim 1, characterized in that, The determination of the first delivery material based on delivery capacity includes: Receive the delivery instruction and determine the primary delivery location; Determine the cooperative delivery location based on the delivery capacity and the delivery location grouping; The delivery ratio is allocated between the main delivery location and the cooperative delivery location to determine the first delivery material.

5. The dynamic overall distribution system for materials in a mixed-flow workshop as described in claim 1, characterized in that, The dynamic planning and control of material distribution and collaborative distribution locations includes: Identify the initial delivery strategy and determine the first delivery strategy for the main delivery location; Execute the first delivery strategy, traverse the co-delivery locations, and determine the second priority based on the dynamic update of the delivery time window; A second delivery strategy with the second priority is determined, and the delivery order is dynamically planned as the delivery process progresses to complete the delivery of the first delivery material.

6. The dynamic overall distribution system for materials in a mixed-flow workshop as described in claim 5, characterized in that, The dynamic positioning planning during the delivery process includes: The delivery time window is the time interval between the starting node of the delivery location and the node of the minimum safety stock, and the delivery time window is a dynamic window; Interact with the material consumption status of the cooperative delivery location to determine the window bias based on the delivery time window; If the window offset is greater than the preset offset, a strong constraint is applied to the dynamic sorting. If the window offset is less than or equal to the preset offset, a weak constraint is applied to the dynamic sorting.

7. The dynamic coordination and distribution system for materials in a mixed-flow workshop as described in claim 1, characterized in that, The system also includes: If it is a concurrent delivery task, perform delivery collision analysis to locate the delivery collision point; Traverse the delivery collision points and determine the avoidance strategy by dynamically adjusting the order of the delivery locations and adjusting the delivery speed. Based on the aforementioned avoidance strategy, dynamic adjustment and compensation are performed for material distribution.

8. A method for dynamic and coordinated distribution of materials in a mixed-flow workshop, characterized in that, The method is applied to the dynamic overall distribution system for mixed-flow workshop materials as described in claims 1-7, and the method includes: The basic information of the interactive workshop is simplified in terms of information functionality based on material distribution to build a digital workshop. The basic information of the workshop includes the production mode, which is a mixed-flow production mode. Based on the digital workshop, material consumption simulation is performed to determine the minimum safety stock at the line edge by minimizing the delivery slack, and the delivery location grouping is determined by the workstation correlation. The minimum safety stock at the line edge is identified by the line edge inventory location code. Based on the minimum safety stock, a preset delivery time window is pushed forward to generate a delivery instruction. Combined with the delivery location grouping, the first delivery material based on the delivery capacity is determined. Upon receiving the delivery instruction, and in conjunction with the first delivery material, an initial delivery strategy is determined, wherein the initial delivery strategy prioritizes the primary delivery location. The initial delivery strategy is transmitted to the material delivery system for dynamic planning and control of material delivery and cooperative delivery locations.

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