An agv cross-factory collaborative operation control method

Abstract

This invention provides a method for controlling cross-plant collaborative operations of AGVs, belonging to the field of AGV collaborative control technology. The method includes: acquiring AGV operation planning data; performing cross-plant collaborative adjustment analysis based on adjacent plants to form adjacent plant collaborative operation adjustment data; acquiring material transportation demand change data; combining it with AGV operation planning data to perform cross-plant scheduling collaborative analysis to form cross-plant scheduling collaborative adjustment data; and combining the adjacent plant collaborative operation adjustment data and the cross-plant scheduling collaborative adjustment data to perform collaborative operation control processing to form cross-plant collaborative operation control data. This method improves the efficiency of cross-plant collaborative operations and effectively saves costs by performing AGV cross-plant collaborative control processing from the perspective of the overall production operation.

Description

Technical Field

[0001] This invention relates to the field of AGV collaborative control technology, and in particular to a method for controlling AGV collaborative operations across factory areas. Background Technology

[0002] AGVs (Automated Guided Vehicles) are intelligent logistics devices based on automated navigation technology, widely used in various industries to greatly improve material transportation efficiency and reduce labor costs. With societal development, the demand for coordinated control of AGV clusters is increasing.

[0003] Currently, in order to achieve automation and intelligence in production, more and more companies are using AGV clusters for collaborative operations between different processes or even between factory areas. Most of these collaborative operations are mainly carried out between single processes or between two fixed related factory areas, without considering the collaboration from the perspective of the entire production system or the entire production process. This results in the inability to achieve more efficient and orderly scheduling of AGVs at the overall level to complete more effective cross-factory collaborative control operations.

[0004] Therefore, designing a control method for cross-plant collaborative operation of AGVs, and improving the efficiency of cross-plant collaborative operation and effectively saving costs by carrying out collaborative control processing of AGVs across the entire production operation, is an urgent problem to be solved. Summary of the Invention

[0005] This invention provides a method for controlling AGV collaborative operations across factory areas.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: Firstly, a method for controlling cross-plant collaborative operations of AGVs is provided. The method includes: acquiring AGV operation planning data, performing cross-plant collaborative adjustment analysis based on adjacent plants, and forming adjacent plant collaborative operation adjustment data; acquiring material transportation demand change data, combining it with AGV operation planning data to perform cross-plant scheduling collaborative analysis, and forming cross-plant scheduling collaborative adjustment data; and combining adjacent plant collaborative operation adjustment data and cross-plant scheduling collaborative adjustment data to perform collaborative operation control processing, and forming cross-plant collaborative operation control data.

[0007] Therefore, the above method first performs cross-regional collaborative planning and adjustment analysis on the current AGV collaborative operation planning data between adjacent factory areas, integrates AGV resources between adjacent factory areas for more efficient collaborative control, and improves the cross-factory collaborative efficiency between adjacent factory areas. At the same time, it considers the changes in AGV resources between different factory areas based on changes in material transportation demand, and performs cross-factory AGV scheduling and collaboration, especially between non-adjacent factory areas. Under the condition of meeting the material transportation demand of the corresponding factory area, it performs overall AGV resource scheduling and collaboration on the production system, which greatly improves the efficient utilization of AGV resources in the entire production system, while also ensuring the reasonable and effective response to changes in material transportation demand in different factory areas.

[0008] Optionally, AGV operation planning data is acquired, and cross-regional collaborative adjustment analysis based on adjacent factory areas is performed to form adjacent factory area collaborative operation adjustment data, including: acquiring unit operation planning information corresponding to different AGVs in different factory areas based on AGV operation planning data; performing collaborative adjustment analysis based on operation efficiency for any two adjacent factory areas in combination with the corresponding unit operation planning information of different AGVs to form adjacent factory area collaborative adjustment analysis results; and aggregating the collaborative adjustment analysis results of different adjacent factory areas to form adjacent factory area collaborative operation adjustment data.

[0009] Therefore, the main purpose of adjusting cross-regional collaborative operations between adjacent factory areas based on AGV operation planning data is to further improve the efficiency of AGV operations, reduce the material transportation waiting time within the factory area, and thus improve operational efficiency from the perspective of saving material transportation time. Based on this, it is first necessary to understand the future material transportation operation plans of AGVs within the factory area, and then combine the planning data to conduct cross-regional collaboration between AGVs in adjacent factory areas to reduce material transportation waiting time. It is understandable that this cross-regional collaborative control is mainly aimed at adjacent factory areas, since scheduling AGVs from non-adjacent factory areas is neither conducive to saving AGV energy consumption nor to controlling time efficiency. It should be noted that the factory areas considered in this application are mainly divided into areas based on process requirements; of course, direct physical division of factory areas certainly conforms to the collaborative method considerations of this application.

[0010] Optionally, for any two adjacent plant areas, a collaborative adjustment analysis based on operational efficiency is performed using the unit operation planning information of the corresponding different AGVs to form a collaborative adjustment analysis result for adjacent plant areas. This includes: according to the process sequence of adjacent plant areas, performing a material substitution analysis based on the subsequent plant area for different AGVs in the preceding plant area according to the unit operation planning information corresponding to different AGVs, forming material substitution analysis result data; obtaining the material substitution analysis result data corresponding to different AGVs in the preceding plant area, performing substitution interference analysis, and forming a collaborative adjustment analysis result for adjacent plant areas.

[0011] Therefore, the collaborative adjustment analysis of adjacent factory areas includes two aspects. Firstly, it determines whether the AGVs from the previous process can interchange with AGVs in adjacent factory areas for material handling operations, and whether this interchange can further reduce waiting time and transportation time for the next material handling operation. Secondly, since cross-regional interchange operations involve different AGVs, it is necessary to assess whether there are any temporal or spatial interferences in the interchange scenarios to avoid collaborative adjustment errors and ensure that the analysis results can be practically applied to achieve efficient collaborative operations between adjacent factory areas. It should be noted that this interchangeability analysis should be based on the process sequence, as subsequent processes generally should not affect the production efficiency of preceding processes.

[0012] Optionally, according to the process sequence of adjacent plant areas, and based on the unit operation planning information corresponding to different AGVs, a material transportation substitution analysis is performed on different AGVs in the preceding plant area based on the subsequent plant area, forming material transportation substitution analysis result data, including: determining the planned return arrival time and planned material transportation time after the object returns for the unit operation planning information corresponding to different AGVs in the subsequent plant area; determining the planned material transportation arrival time and planned return arrival time for the object for the unit operation planning information corresponding to different AGVs in the preceding plant area; and performing material transportation substitution analysis on different AGVs in the preceding plant area in the following manner: marking the AGV to be replaced as the AGV to be replaced, and based on the planned material transportation arrival time and adjacent plant areas of the AGV to be replaced... The average cross-regional scheduling time determines the corresponding planned cross-regional arrival time of the object. Based on the planned cross-regional arrival time of the object and the planned material transportation time of the object after return from different AGVs in the subsequent plant area, the AGVs that are adjacent to and follow the planned cross-regional arrival time of the object are identified as the AGVs to be replaced. If the time difference between the planned replacement return arrival time of the AGV to be replaced, determined by the corresponding planned return arrival time of the object, the average scheduling time of adjacent cross-regional areas, and the planned return time of the object to be replaced, and the planned return arrival time of the object corresponding to the AGV to be replaced, does not exceed the allowable time difference for replacement return, then the AGV to be replaced and the AGV to be replaced are identified as a cross-regional material transportation replacement object group.

[0013] Therefore, the material transportation substitution analysis between adjacent plant areas determines whether the preceding AGV can immediately cross over to transport materials to the adjacent plant area after completing its current material transport, replacing the AGVs in the subsequent plant area that would perform their transport work earlier. Of course, the AGV being replaced in the subsequent plant area also needs to be able to return to the preceding plant area's transport point within the allowed arrival time difference. This improves the efficiency of material transportation operations in the subsequent plant area to a certain extent, ensures the timely execution of operations in the preceding plant area, and avoids the imbalance in AGV resource allocation caused by one-way cross-plant material transportation. It can be understood that the substitution analysis needs to be based on the AGVs in the preceding plant area, directly confirming whether the AGVs corresponding to adjacent material transport times in the subsequent plant area can be substituted. Alternatively, substitution analysis can be performed on multiple adjacent AGVs, as long as the time of return of the replaced AGV to the preceding plant area is within the allowed time range. Essentially, the allowed return time difference for substitution should be less than the lead time for the AGV to transport materials to the subsequent plant area in advance, thus achieving more efficient material transportation operations in the subsequent plant area.

[0014] Optionally, the material transportation replacement analysis results data corresponding to different AGVs in the preceding plant area are obtained, and replacement interference analysis is performed to form the collaborative adjustment analysis results of adjacent plants. This includes: performing object intersection analysis on any two groups based on different cross-regional material transportation replacement object groups in the preceding plant area; if there are the same AGV to be replaced for any two cross-regional material transportation replacement object groups, then the cross-regional material transportation replacement object group with the larger difference between the time point of the AGV to be replaced transporting materials across regions and the time point of the AGV to be replaced transporting materials is retained; and all remaining cross-regional material transportation replacement object groups are combined to form the corresponding collaborative adjustment analysis results of adjacent plants.

[0015] Therefore, the purpose of interference analysis is to avoid situations where the selected AGV to be replaced is the same AGV in the cross-regional material transportation replacement object group extracted from adjacent plants. This would cause difficulties in the actual implementation of subsequent cross-regional replacement operations, leading to larger collaborative control problems. The interference analysis method involves comparing and analyzing whether the AGVs to be replaced in the object groups formed by different AGVs from the preceding plants in adjacent plants are the same. Of course, the replacement analysis adopted in this application only involves replacing the AGVs in the subsequent plants immediately after the planned material transportation time of the AGV to be replaced, which greatly reduces the possibility of interference. However, if we consider whether multiple AGVs in the subsequent plants can be replaced after the arrival time of the AGV to be replaced in the cross-regional collaborative mode, the probability of interference is relatively high. Therefore, interference analysis is a key element for the successful implementation of cross-regional collaborative control between adjacent plants.

[0016] Optionally, data on changes in material transportation demand can be acquired and combined with AGV operation planning data to conduct cross-regional scheduling collaborative analysis, thereby forming cross-regional scheduling collaborative adjustment data. This includes: analyzing the AGV demand in different factory areas based on the data on changes in material transportation demand, thereby forming corresponding factory area AGV demand mapping data; and conducting collaborative analysis based on the shortest cross-regional scheduling path based on the AGV demand mapping data in different factory areas, thereby forming cross-regional scheduling collaborative adjustment data.

[0017] Therefore, for the entire production system, if there are changes in material transportation needs across different processes, the most direct approach is to schedule AGVs from other areas with available AGVs to compensate for the imbalance in AGV configuration caused by these changes. This method effectively avoids the inefficient use of AGVs in processes with surplus AGVs while ensuring the effective fulfillment of material transportation needs in processes with insufficient AGVs, significantly improving operational efficiency and resource utilization. Of course, before implementing cross-regional scheduling, it is necessary to first determine the changes in AGV configuration across different processes based on the changes in demand. Only then can reasonable scheduling and collaborative control be implemented based on these changes. Naturally, to ensure operational efficiency and resource conservation, the scheduling and collaborative analysis is based on planning for the optimal or shortest scheduling path, aiming to achieve the most efficient and energy-saving cross-regional collaborative scheduling operation scheme.

[0018] Optionally, based on the material transportation demand change data, AGV demand analysis is performed for different factory areas to form corresponding factory area AGV demand mapping data, including: determining the change in material transportation demand within different factory areas based on the material transportation demand change data; conducting planning analysis within the material transportation time limit based on the corresponding change in material transportation demand within different factory areas to determine the minimum AGV demand for continuous operation; determining the corresponding factory area AGV supply change based on the corresponding minimum AGV demand and the current number of AGVs for different factory areas; and determining the total supply change based on the corresponding factory area AGV supply change.

[0019] Therefore, when conducting cross-plant scheduling analysis in response to changes in material transportation demand, the first step should be to determine whether the number of AGVs originally in formation within the plant area is sufficient to meet the material transportation requirements within the specified timeframe after the corresponding material transportation changes. This can be determined by planning the material transportation within the plant area. Of course, the material transportation planning aims to minimize the number of AGVs used. Path planning methods are diverse and are currently mature technologies. Planning based on the minimum number of AGVs only requires quantity as the input indicator. Path planning can determine the minimum number of AGVs required to meet the material transportation requirements of the corresponding plant area. The difference between this number and the current number of AGVs in formation within the plant area is the change in AGV supply based on the change in transportation demand. This value can be positive or negative, entirely determined by the change in the material transportation demand of the plant area. Of course, in order to ensure that the subsequent cross-plant scheduling analysis can meet the minimum demand for AGVs in all plants, it is also necessary to determine the total supply change based on the AGV supply change in all plants. After all, there are three possibilities at the overall level: one is that the total supply change is positive, which means that the total number of AGVs can meet the minimum demand of all plants and there is still a surplus; another is that the total supply change is negative, which means that the total number of AGVs cannot provide enough to meet the minimum demand of all plants; and the third is that the total supply change is zero, which means that the total number of AGVs just meets the minimum demand of all plants. The total supply change provides a reference for the number of AGVs to be deactivated or added.

[0020] Optionally, based on the AGV demand mapping data of different factory areas, a collaborative analysis based on the shortest cross-regional scheduling path is performed to form cross-regional scheduling collaborative adjustment data. This includes: confirming the scheduling path between any two factory areas and AGV supply stations to form cross-regional scheduling path data; quantifying cross-regional scheduling based on the changes in AGV supply in different factory areas and the total changes in supply at the overall scheduling points, combined with the cross-regional scheduling path data, to form cross-regional scheduling quantitative data; and performing collaborative analysis based on the shortest cross-regional scheduling path based on the cross-regional scheduling quantitative data to form cross-regional scheduling collaborative adjustment data.

[0021] Therefore, the cross-regional scheduling and collaborative analysis based on the determined changes in AGV supply in different factory areas is mainly aimed at minimizing the total scheduling distance, with the goal of ensuring that scheduling can be achieved in the most efficient way. The challenge in scheduling lies in the fact that the changes in the number of AGVs supplied vary across different factory areas. Some factory areas have enough AGVs to meet the minimum operating requirements, while others have more than enough AGVs, and still others just meet the minimum operating requirements. Furthermore, it is necessary to consider whether more AGVs are being added or recycled at the overall level. Based on this, this application uses a model to quantify the obtained supply changes and the scheduling paths between various factory areas and AGV supply stations, thereby enabling a more direct and efficient analysis.

[0022] Optionally, based on the changes in AGV supply in different factory areas and the total changes in supply at the overall dispatch point, cross-regional dispatching is quantified using cross-regional dispatching path data to form cross-regional dispatching quantitative data. This includes: numerically calibrating different factory areas based on the changes in AGV supply in the factory areas, and numerically calibrating AGV supply stations based on the total changes in supply; determining the dispatching path between any two dispatching locations using the material delivery point of the factory area as the dispatching location point and the inlet / outlet position of the AGV supply station as the dispatching location point; and for any two dispatching locations: determining the directional path from the dispatching location point with the larger calibrated value to the dispatching location point with the smaller calibrated value as the cross-regional supplementary dispatching path; and determining the directional path from the dispatching location point with the smaller calibrated value to the dispatching location point with the larger calibrated value as the cross-regional reduction dispatching path; and combining the calibrated values, cross-regional supplementary dispatching paths, and cross-regional reduction dispatching paths corresponding to different dispatching locations to form cross-regional dispatching quantitative data.

[0023] Therefore, cross-regional scheduling essentially aims to ensure that each factory area has the minimum number of AGVs to meet the changing material transportation needs by minimizing the total path through scheduling. This can be quantified as a path combination model for path selection analysis. This application first determines the location where scheduling occurs within the factory area. Since scheduling always occurs when AGVs are transporting materials, the material arrival point within the factory area is taken as the starting point for scheduling. Then, the path between different scheduling locations is determined. This path can be fixed, as there is no need to focus on path interference with other AGVs between factory areas. Even if path interference occurs, it can be addressed through reasonable spatial and temporal adjustments. This is because the timing of the scheduled AGV's material transportation operation to the destination factory area can be flexibly adjusted, especially with significant temporal redundancy. It can be understood that the scheduling path between factory areas has bidirectional directionality. This directionality determines the change in the calibration values ​​of the scheduling location points. Therefore, confirming the directionality of the path based on the initial calibration values ​​is beneficial for subsequent path direction selection in planning analysis.

[0024] Optionally, based on the cross-regional scheduling quantitative data, a collaborative analysis based on the shortest cross-regional scheduling path is performed to form cross-regional scheduling collaborative adjustment data. This includes: selecting cross-regional supplementary scheduling paths and cross-regional reduction scheduling paths according to the calibration values ​​corresponding to different scheduling locations. The selection specification is as follows: for each cross-regional supplementary scheduling path selected at the corresponding scheduling location, the calibration value is decremented by one; for each cross-regional reduction scheduling path selected at the corresponding scheduling location, the calibration value is incremented by one. For any scheduling location, the following must be satisfied: the calibration value is calculated based on the number of selected associated cross-regional supplementary scheduling paths and cross-regional reduction scheduling paths, making the calculated value zero. The combination with the shortest total distance among the different combinations of cross-regional supplementary scheduling paths and cross-regional reduction scheduling paths that meet the requirements, along with the supply quantity of the corresponding AGV supply station, is determined as the cross-regional scheduling collaborative adjustment data.

[0025] Therefore, cross-regional scheduling and collaborative analysis based on quantified data mainly involves selecting scheduling paths. The essence of path selection is to achieve AGV scheduling between different factory areas. The result of path selection is to ensure that the change in AGV supply at each scheduling location point becomes zero. This is necessary to achieve a balance between the overall number of AGVs and the demand of each factory area. It's understandable that path selection might involve rescheduling AGVs in factories that have already met their minimum demand, causing them to fall below the minimum requirement. For this approach, it's advisable to consider whether to temporarily provide AGVs for timely replenishment based on planning analysis, or to consider setting restrictions so that the number of AGVs in the corresponding factory area cannot be adjusted once the minimum demand is reached. Of course, such restrictions will increase the total scheduling distance to some extent. Without such restrictions, scheduling planning, especially material transportation planning within the factory area, becomes more complex. Both methods can be considered comprehensively based on the actual situation. For cross-regional scheduling, there are various combinations of path selection methods. Finally, using the path with the shortest total distance as the result can ensure the efficiency of cross-regional scheduling and save resources to some extent. Attached Figure Description

[0026] Figure 1 A schematic diagram of the architecture of an AGV cross-factory collaborative operation control system provided in an embodiment of the present invention; Figure 2 A flowchart illustrating an AGV cross-factory collaborative operation control method provided in an embodiment of the present invention; Figure 3 This invention provides a flowchart of the cross-regional adjustment process for an AGV cross-plant collaborative operation control method. Figure 4 This is a schematic diagram of the structure of an AGV cross-factory collaborative operation control system provided in an embodiment of the present invention. Detailed Implementation

[0027] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0028] In this embodiment of the invention, "instruction" can include direct and indirect instructions, as well as explicit and implicit instructions. The information indicated by a certain piece of information is called the information to be instructed. In specific implementation, there are many ways to instruct the information to be instructed, such as, but not limited to, directly instructing the information to be instructed, such as the information to be instructed itself or its index. It can also indirectly instruct the information to be instructed by instructing other information, where there is a correlation between the other information and the information to be instructed. It can also instruct only a part of the information to be instructed, while the other parts are known or pre-agreed upon. For example, the instruction of specific information can be achieved by using a pre-agreed (e.g., protocol-defined) arrangement of various pieces of information, thereby reducing instruction overhead to some extent. Simultaneously, common parts of various pieces of information can be identified and uniformly indicated to reduce the instruction overhead caused by individually indicating the same information.

[0029] Furthermore, the specific indication method can also be any existing indication method, such as, but not limited to, the above-mentioned indication methods and their various combinations. Specific details of various indication methods can be found in existing technologies, and will not be elaborated upon here. As described above, for example, when multiple pieces of information of the same type need to be indicated, the indication methods for different pieces of information may differ. In specific implementation, the required indication method can be selected according to specific needs. This embodiment of the invention does not limit the selected indication method; therefore, the indication methods involved in this embodiment of the invention should be understood to cover various methods that enable the party to be indicated to obtain the information to be indicated.

[0030] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information messages sent separately, and the sending period and / or timing of these sub-information messages can be the same or different. The specific sending method is not limited in this embodiment of the invention. The sending period and / or timing of these sub-information messages can be predefined, for example, according to a protocol, or configured by the sending device by sending configuration information to the receiving device.

[0031] "Predefined" or "pre-configured" can be achieved by pre-saving corresponding codes, tables, or other means that can be used to indicate relevant information in the device. This embodiment of the invention does not limit the specific implementation method. "Saving" can refer to saving in one or more memories. These memories can be separate installations or integrated into the encoder, decoder, processor, or processing device. Alternatively, some memories can be separately installed, while others are integrated into the decoder, processor, or processing device. The type of memory can be any form of storage medium, and this embodiment of the invention does not limit this.

[0032] In this embodiment of the invention, descriptions such as "when," "under the circumstances," "if," and "if" all refer to the device making corresponding processing under certain objective circumstances, and are not limited to a specific time. They do not require the device to make a judgment action during implementation, nor do they imply any other limitations.

[0033] In the description of the embodiments of the present invention, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can represent A or B. "And / or" in the embodiments of the present invention is merely a description of the relationship between the related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. Furthermore, in the description of the embodiments of the present invention, unless otherwise stated, "multiple" refers to two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. Additionally, to facilitate a clear description of the technical solutions of the embodiments of the present invention, the terms "first" and "second" are used in the embodiments of the present invention to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first," "second," etc., do not limit the quantity or order of execution, and that "first," "second," etc., are not necessarily different. Furthermore, in the embodiments of this invention, words such as "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this invention should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner for ease of understanding.

[0034] To facilitate understanding of the embodiments of the present invention, firstly, let's take... Figure 1 The AGV cross-factory collaborative operation control system shown in the figure is used as an example to illustrate the AGV cross-factory collaborative operation control method applicable to the embodiments of the present invention.

[0035] For example, Figure 1 This is a schematic diagram of the architecture of an AGV cross-factory collaborative operation control system provided in an embodiment of the present invention. Figure 1 As shown, the system may include a control system and AGV equipment.

[0036] Figure 2 This is a flowchart illustrating an AGV cross-factory collaborative operation control method provided by an embodiment of the present invention. Figure 3 This is a schematic diagram illustrating the cross-regional adjustment process of an AGV cross-plant collaborative operation control method provided in an embodiment of the present invention. This AGV cross-plant collaborative operation control method is applicable to the aforementioned system, and the specific process is as follows: S1: Obtain AGV operation planning data, perform cross-regional collaborative adjustment analysis based on adjacent factory areas, and generate collaborative operation adjustment data for adjacent factory areas.

[0037] Acquire AGV operation planning data, conduct cross-regional collaborative adjustment analysis based on adjacent factory areas, and form adjacent factory area collaborative operation adjustment data, including: obtaining unit operation planning information corresponding to different AGVs in different factory areas based on AGV operation planning data; conducting collaborative adjustment analysis based on operation efficiency for any two adjacent factory areas and combining the corresponding unit operation planning information of different AGVs to form adjacent factory area collaborative adjustment analysis results; and aggregating the collaborative adjustment analysis results of different adjacent factory areas to form adjacent factory area collaborative operation adjustment data.

[0038] The main purpose of adjusting cross-regional collaborative operations between adjacent factory areas based on AGV operation planning data is to further improve the efficiency of AGV operations, reduce the waiting time for material transportation within the factory area, and thus improve operational efficiency from the perspective of saving material transportation time. Based on this, it is first necessary to understand the future material transportation operation plans of AGVs within the factory area, and then combine the planning data to implement cross-regional collaboration between AGVs in adjacent factory areas to reduce material transportation waiting time. It is understandable that this type of cross-regional collaborative control mainly targets adjacent factory areas, since scheduling AGVs from non-adjacent factory areas is neither conducive to saving AGV energy consumption nor to controlling time efficiency. It should be noted that the factory areas considered in this application are mainly divided into areas based on process requirements; however, direct physical division of factory areas certainly conforms to the collaborative method considerations of this application.

[0039] For any two adjacent plant areas, a collaborative adjustment analysis based on operational efficiency is performed using the unit operation planning information of the corresponding different AGVs to form the collaborative adjustment analysis results of adjacent plant areas. This includes: according to the process sequence of adjacent plant areas, performing material substitution analysis on different AGVs in the preceding plant area based on the unit operation planning information of different AGVs, forming material substitution analysis result data; obtaining the material substitution analysis result data corresponding to different AGVs in the preceding plant area, performing substitution interference analysis, and forming the collaborative adjustment analysis results of adjacent plant areas.

[0040] The collaborative adjustment analysis between adjacent plant areas includes two aspects. First, it determines whether AGVs from the previous process can interchange with AGVs in adjacent plant areas for material handling operations, and whether this interchange can further reduce waiting time and transportation time for subsequent material handling. Second, since cross-regional interchange operations involve different AGVs, it's necessary to assess whether there are any temporal or spatial interferences in these interchanges to avoid collaborative adjustment errors and ensure the analysis results can be practically applied to achieve efficient collaborative operations between adjacent plant areas. It should be noted that this interchangeability analysis should be based on the process sequence, as subsequent processes typically should not affect the production efficiency of preceding processes.

[0041] Following the process sequence of adjacent plant areas, and based on the unit operation planning information corresponding to different AGVs, a material transportation substitution analysis is performed on different AGVs in the preceding plant area based on the subsequent plant area. This results in material transportation substitution analysis data, including: determining the planned return arrival time and planned material transportation time after the object's return for the unit operation planning information corresponding to different AGVs in the subsequent plant area; determining the planned material transportation arrival time and planned return arrival time for the object corresponding to the unit operation planning information corresponding to different AGVs in the preceding plant area; and performing material transportation substitution analysis on different AGVs in the preceding plant area in the following manner: marking the AGVs to be analyzed as the AGVs to be replaced, and based on the planned material transportation arrival time of the object corresponding to the AGV to be replaced and the adjacent cross-area... The average scheduling time determines the corresponding planned cross-regional arrival time of the object. Based on the planned cross-regional arrival time of the object and the planned material transportation time of different AGVs in the subsequent plant area after the object returns, the AGVs that are adjacent to and follow the planned cross-regional arrival time of the object in the time dimension are identified and recorded as the AGVs to be replaced. If the time difference between the planned replacement return arrival time of the AGV to be replaced, determined by the corresponding planned return arrival time of the object, the average scheduling time of adjacent cross-regional areas, and the planned return time of the object to be replaced, and the planned return arrival time of the object corresponding to the AGV to be replaced, does not exceed the allowable time difference for replacement return, then the AGV to be replaced and the AGV to be replaced are identified as a cross-regional material transportation replacement object group.

[0042] The material transport substitution analysis between adjacent plant areas determines whether a preceding AGV can immediately cross over to transport materials to an adjacent plant area after completing its transport, replacing the AGVs in subsequent plants that would perform their transport tasks earlier. Of course, the replaced AGV in the subsequent plant area also needs to be able to return to the preceding plant's transport point within the allowed arrival time difference. This improves the efficiency of material transport operations in the subsequent plant area to some extent, ensures the timely execution of operations in the preceding plant area, and avoids AGV resource allocation imbalances caused by one-way cross-plant transport. It's understandable that the substitution analysis needs to be based on the AGVs in the preceding plant area, directly confirming whether the AGVs corresponding to adjacent transport times in the subsequent plant area can be substituted. Alternatively, substitution analysis can be performed on multiple adjacent AGVs, as long as the return time of the replaced AGV to the preceding plant area is within the allowed time range. Essentially, the allowed return time difference for substitution should be less than the lead time for the replacing AGV to transport materials to the subsequent plant area in advance, thus achieving more efficient material transport operations in the subsequent plant area.

[0043] Obtain the material transportation replacement analysis results data corresponding to different AGVs in the preceding plant area, perform replacement interference analysis, and form the adjacent plant area collaborative adjustment analysis results, including: based on the different cross-regional material transportation replacement object groups in the preceding plant area, perform object intersection analysis of any two groups: if for any two cross-regional material transportation replacement object groups, there are the same AGV to be replaced, then retain the cross-regional material transportation replacement object group with the larger difference between the time point when the AGV to be replaced crosses the region to transport materials and the time point when the AGV to be replaced transports materials; gather all the remaining cross-regional material transportation replacement object groups to form the corresponding adjacent plant area collaborative adjustment analysis results.

[0044] The purpose of interference analysis is to avoid situations where the selected AGV to be replaced is the same AGV in the cross-regional material transportation replacement object groups extracted from adjacent plants. This would cause difficulties in the actual implementation of subsequent cross-regional replacement operations, leading to larger collaborative control problems. Interference analysis involves comparing the object groups formed by different AGVs from preceding plants in adjacent plants to determine if the AGVs to be replaced are identical. While this application only analyzes the replacement of AGVs in the subsequent plant immediately after the planned material transportation time, significantly reducing the possibility of interference, the probability of interference increases when considering cross-regional collaboration methods where multiple AGVs in the subsequent plant can be replaced after the arrival time of the AGV to be replaced. Therefore, interference analysis is crucial for the successful implementation of cross-regional collaborative control between adjacent plants.

[0045] S2: Obtain data on changes in material transportation demand, combine it with AGV operation planning data to conduct cross-regional scheduling collaborative analysis, and generate cross-regional scheduling collaborative adjustment data.

[0046] Acquire material transportation demand change data, combine it with AGV operation planning data to conduct cross-regional scheduling collaborative analysis, and form cross-regional scheduling collaborative adjustment data, including: based on the material transportation demand change data, analyze the AGV demand of different plant areas to form corresponding plant area AGV demand mapping data; based on the AGV demand mapping data of different plant areas, conduct collaborative analysis based on the shortest cross-regional scheduling path to form cross-regional scheduling collaborative adjustment data.

[0047] For the entire production system, if material transportation needs change across different processes, the most direct approach is to schedule AGVs from other areas with available AGVs to compensate for the imbalance in AGV configuration caused by these changes. This method effectively avoids the inefficient use of AGVs in processes with surplus AGVs while ensuring the material transportation needs of processes with insufficient AGVs are met, significantly improving operational efficiency and resource utilization. Of course, before implementing cross-regional scheduling, it's necessary to determine the changes in AGV configuration across different processes based on demand variations. Only then can reasonable scheduling and collaborative control be implemented based on these changes. To ensure operational efficiency and resource conservation, the scheduling and collaborative analysis focuses on planning for the optimal or shortest possible scheduling path, aiming to achieve the most efficient and energy-saving cross-regional collaborative scheduling operation scheme.

[0048] Based on the data on changes in material transportation demand, an analysis of AGV demand in different factory areas is conducted to generate corresponding AGV demand mapping data for each factory area. This includes: determining the changes in material transportation demand within each factory area based on the data; conducting planning analysis within the material transportation timeframe based on the changes in material transportation demand within each factory area to determine the minimum AGV demand for continuous operation; determining the changes in AGV supply for each factory area based on the corresponding minimum AGV demand and the current number of AGVs; and determining the total changes in supply based on the changes in AGV supply for each factory area.

[0049] When conducting cross-plant scheduling analysis in response to changes in material transportation demand, the first step should be to determine whether the number of AGVs originally in formation within the plant area is sufficient to meet the material transportation requirements within the specified timeframe after the corresponding material transportation changes. This can be determined by planning the material transportation within the plant area. Of course, the material transportation planning aims to minimize the number of AGVs used. There are various methods for path planning, which is a mature technology, and planning based on the minimum number of AGVs only requires quantity as the input indicator. Through path planning, the minimum number of AGVs required to meet the material transportation requirements of the corresponding plant area can be determined. The difference between this number and the current number of AGVs in formation within the plant area is the change in AGV supply based on the change in transportation demand. This value can be positive or negative, entirely determined by the change in material transportation demand within the plant area. Of course, in order to ensure that the subsequent cross-plant scheduling analysis can meet the minimum demand for AGVs in all plants, it is also necessary to determine the total supply change based on the AGV supply change in all plants. After all, there are three possibilities at the overall level: one is that the total supply change is positive, which means that the total number of AGVs can meet the minimum demand of all plants and there is still a surplus; another is that the total supply change is negative, which means that the total number of AGVs cannot provide enough to meet the minimum demand of all plants; and the third is that the total supply change is zero, which means that the total number of AGVs just meets the minimum demand of all plants. The total supply change provides a reference for the number of AGVs to be deactivated or added.

[0050] Based on the AGV demand mapping data of different factory areas, a collaborative analysis based on the shortest cross-regional scheduling path is conducted to form cross-regional scheduling collaborative adjustment data. This includes: confirming the scheduling path between any two factory areas and AGV supply stations to form cross-regional scheduling path data; quantifying cross-regional scheduling based on the changes in AGV supply in different factory areas and the total changes in supply at the overall scheduling points, combined with the cross-regional scheduling path data, to form cross-regional scheduling quantitative data; and conducting collaborative analysis based on the shortest cross-regional scheduling path based on the cross-regional scheduling quantitative data to form cross-regional scheduling collaborative adjustment data.

[0051] The cross-regional scheduling and collaborative analysis based on the determined changes in AGV supply across different factory areas primarily aims to minimize the total scheduling distance, ensuring the most efficient scheduling. The challenge lies in the varying AGV supply changes across different factory areas. Some areas have enough AGVs to meet the minimum operational requirements, while others have more than enough, and still others just meet the minimum requirements. Furthermore, it's crucial to consider whether the overall supply of AGVs is primarily new or recycled. Therefore, this application quantifies the obtained supply changes and the scheduling paths between various factory areas and AGV supply stations using a model, enabling a more direct and efficient analysis.

[0052] Based on the changes in AGV supply in different factory areas and the total changes in supply at the overall dispatch points, cross-regional dispatch is quantified using cross-regional dispatch path data to form cross-regional dispatch quantification data. This includes: numerically calibrating different factory areas based on changes in AGV supply, and numerically calibrating AGV supply stations based on total changes in supply; determining dispatch paths for any two dispatch locations using the material delivery point in the factory area as the dispatch location point and the inlet / outlet position of the AGV supply station as the dispatch location point; and for any two dispatch locations: determining the direction path from the dispatch location point with the larger calibrated value to the dispatch location point with the smaller calibrated value as the cross-regional supplementary dispatch path; and determining the direction path from the dispatch location point with the smaller calibrated value to the dispatch location point with the larger calibrated value as the cross-regional reduction dispatch path; and combining the calibrated values, cross-regional supplementary dispatch paths, and cross-regional reduction dispatch paths corresponding to different dispatch locations to form cross-regional dispatch quantification data.

[0053] Cross-regional scheduling essentially aims to ensure that each factory area has the minimum number of AGVs to meet changing material transportation needs by minimizing the total path length through scheduling. Therefore, it can be quantified as a path combination model for path selection analysis. This application first determines the location where scheduling occurs within the factory area. Since scheduling always occurs when AGVs are transporting materials, the material arrival point within the factory area is taken as the starting point for scheduling. Then, the paths between different scheduling locations are determined. These paths can be fixed, as there's no need to focus on path interference with other AGVs between factory areas. Even if path interference occurs, it can be addressed through reasonable spatial and temporal adjustments. This is because the timing of the scheduled AGV's material transportation operation to the destination factory area can be flexibly adjusted, especially with significant temporal redundancy. It's understood that the scheduling paths between factory areas have bidirectional directionality. This directionality determines the changes in the calibration values ​​of the scheduling locations. Therefore, confirming the directionality of the path based on the initial calibration values ​​is beneficial for subsequent path direction selection in planning analysis.

[0054] Based on the quantitative data of cross-regional scheduling, a collaborative analysis based on the shortest cross-regional scheduling path is conducted to form cross-regional scheduling collaborative adjustment data. This includes: selecting cross-regional supplementary scheduling paths and cross-regional reduction scheduling paths according to the calibration values ​​corresponding to different scheduling locations. The selection specification is as follows: for each cross-regional supplementary scheduling path selected at the corresponding scheduling location, the calibration value is decreased by one; for each cross-regional reduction scheduling path selected at the corresponding scheduling location, the calibration value is increased by one. For any scheduling location, the following must be satisfied: the calibration value is calculated based on the number of selected associated cross-regional supplementary scheduling paths and cross-regional reduction scheduling paths, so that the calculated value is zero. The combination with the shortest total distance among the different combinations of cross-regional supplementary scheduling paths and cross-regional reduction scheduling paths that meet the requirements, along with the supply quantity of the corresponding AGV supply station, is determined as the cross-regional scheduling collaborative adjustment data.

[0055] Cross-regional scheduling and collaborative analysis based on quantified data primarily involves selecting scheduling paths. The essence of path selection is to achieve AGV scheduling between different factory areas. The result of path selection is to ensure that the change in AGV supply at each scheduling location point becomes zero. This achieves a balance between the overall AGV quantity and the demand of each factory area. It's understandable that path selection might involve rescheduling AGVs in factories that have already met their minimum demand, causing them to fall below the minimum requirement. For this approach, it's advisable to consider whether to temporarily provide AGVs for timely replenishment based on planning analysis, or to consider setting restrictions so that the number of AGVs in the corresponding factory area cannot be adjusted once the minimum demand is reached. Of course, such restrictions will increase the total scheduling distance to some extent. Without such restrictions, scheduling planning, especially material transportation planning within the factory area, becomes more complex. Both methods can be considered comprehensively based on the actual situation. For cross-regional scheduling, there are various combinations of path selection methods. Finally, using the path with the shortest total distance as the result ensures the efficiency of cross-regional scheduling and can also save resources to some extent.

[0056] S3: Combine the collaborative operation adjustment data of adjacent plant areas and the collaborative adjustment data of cross-regional scheduling to perform collaborative operation control processing, and form cross-plant collaborative operation control data.

[0057] The collaborative operation control processing of the resulting adjustment data mainly involves integrating all cross-plant area scheduling information into the current path planning data for further planning and analysis, eliminating spatial and temporal interference based on the planning data, and forming feasible collaborative operation control data.

[0058] Figure 4This is a schematic diagram of the structure of an AGV cross-factory collaborative operation control system provided in an embodiment of the present invention. Exemplarily, this system can be a network device, or a chip (system) or other component or assembly that can be configured within the network device. Figure 4 As shown, the processing equipment includes a data acquisition unit for acquiring AGV operation planning data and material transportation demand change data; a cross-regional collaborative analysis unit for performing cross-regional collaborative adjustment analysis on the AGV operation planning data acquired by the data acquisition unit based on adjacent plant areas, forming adjacent plant area collaborative operation adjustment data, and combining it with material transportation demand change data to perform cross-regional scheduling collaborative analysis, forming cross-regional scheduling collaborative adjustment data; and a collaborative operation control unit for performing collaborative operation control processing on the cross-regional scheduling collaborative adjustment data and adjacent plant area collaborative operation adjustment data formed by the cross-regional collaborative analysis unit, forming cross-plant area collaborative operation control data.

[0059] This system collects basic data for cross-plant collaborative operation analysis through different data acquisition units. The cross-plant collaborative analysis unit then performs replacement and coordination analysis between adjacent plants, as well as cross-plant collaborative operation adjustment analysis at the entire production system level. Finally, the collaborative operation control unit generates control information based on the analysis results to implement cross-plant collaborative control. The different units are interconnected, forming a tightly integrated whole capable of cross-plant collaborative operation control, which is a crucial material foundation for achieving cross-plant collaborative control.

[0060] It should be understood that, in the embodiments of the present invention, the unit with data processing function can be a central processing unit (CPU). This processor can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0061] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0062] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0063] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0064] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0065] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0066] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0067] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0068] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0069] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0070] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for controlling AGV cross-factory collaborative operations, characterized in that, The method includes: Acquire AGV operation planning data, conduct cross-regional collaborative adjustment analysis based on adjacent factory areas, and generate collaborative operation adjustment data for adjacent factory areas; Acquire data on changes in material transportation demand, and combine this data with the AGV operation planning data to conduct cross-regional scheduling and collaborative analysis, thereby generating cross-regional scheduling and collaborative adjustment data. By combining the adjacent plant area collaborative operation adjustment data and the cross-regional scheduling collaborative adjustment data, collaborative operation control processing is performed to form cross-plant area collaborative operation control data.

2. The method according to claim 1, characterized in that, The process of acquiring AGV operation planning data, performing cross-regional collaborative adjustment analysis based on adjacent factory areas, and generating adjacent factory area collaborative operation adjustment data includes: Based on the AGV operation planning data, obtain the unit operation planning information corresponding to different AGVs in different factory areas; For any two adjacent factory areas, a collaborative adjustment analysis based on work efficiency is performed by combining the unit operation planning information of the corresponding different AGVs to form the collaborative adjustment analysis results of adjacent factory areas; The results of the collaborative adjustment analysis of different adjacent plant areas are combined to form the collaborative operation adjustment data of the adjacent plant areas.

3. The method according to claim 2, characterized in that, The step of performing a collaborative adjustment analysis based on work efficiency for any two adjacent factory areas, combined with the unit operation planning information of the corresponding different AGVs, to form a collaborative adjustment analysis result for adjacent factory areas, includes: According to the process sequence of adjacent plant areas, based on the unit operation planning information corresponding to different AGVs, material transportation replacement analysis is performed on different AGVs in the preceding plant area based on the subsequent plant area to form material transportation replacement analysis result data. The material transportation replacement analysis results data corresponding to different AGVs in the preceding plant area are obtained, and replacement interference analysis is performed to form the collaborative adjustment analysis results of the adjacent plant areas.

4. The method according to claim 3, characterized in that, The process involves performing a material substitution analysis on different AGVs in the preceding plant area based on the unit operation planning information corresponding to different AGVs, according to the process sequence of adjacent plant areas, to generate material substitution analysis result data, including: For the unit operation planning information corresponding to different AGVs in the subsequent plant area, determine the corresponding planned return arrival time of the object and the planned material transportation time after the object returns; For the unit operation planning information corresponding to different AGVs in the preceding plant area, determine the corresponding planned material delivery time and planned return time of the object. The following material handling substitution analysis was performed on different AGVs in the preceding plant area: The AGVs being analyzed are labeled as AGVs to be replaced. Based on the planned arrival time of the object corresponding to the AGV to be replaced and the average scheduling time of adjacent cross-regional areas, the corresponding planned cross-regional arrival time of the object is determined. Based on the planned arrival time of the object across the region and the planned material transport time of the object after the return of different AGVs in the subsequent factory area, the AGVs that are adjacent to and follow the planned material transport time of the object after the return of the object in the time dimension are identified and recorded as the AGVs to be replaced. If the time difference between the planned replacement return arrival time of the AGV to be replaced, determined by the corresponding planned return arrival time of the object, the average scheduling time of adjacent cross-regional transport, and the planned return time of the object of the AGV to be replaced, and the planned return arrival time of the object corresponding to the AGV to be replaced does not exceed the allowable time difference for replacement return, then the AGV to be replaced and the AGV to be replaced are determined as a cross-regional material transportation replacement object group.

5. The method according to claim 4, characterized in that, The process of acquiring the material replacement analysis results data corresponding to different AGVs in the preceding plant area, performing replacement interference analysis, and forming the collaborative adjustment analysis results of adjacent plant areas includes: Based on the different cross-regional material transportation replacement object groups in the preceding plant area, perform object intersection analysis on any two groups: If any two cross-regional material transportation replacement object groups have the same AGV to be replaced, then the cross-regional material transportation replacement object group with the larger difference between the time point when the AGV to be replaced is transporting materials across regions and the time point when the AGV to be replaced is transporting materials will be retained. The remaining cross-regional material transportation replacement object groups are aggregated to form the corresponding adjacent plant area collaborative adjustment analysis results.

6. The method according to claim 5, characterized in that, The process of acquiring material transportation demand change data and combining it with AGV operation planning data to perform cross-regional scheduling collaborative analysis, forming cross-regional scheduling collaborative adjustment data, includes: Based on the material transportation demand change data, AGV demand analysis is performed in different factory areas to form corresponding factory area AGV demand mapping data. Based on the AGV demand mapping data of different factory areas, a collaborative analysis based on the shortest cross-regional scheduling path is performed to form the cross-regional scheduling collaborative adjustment data.

7. The method according to claim 6, characterized in that, Based on the material transportation demand change data, the AGV demand analysis for different factory areas is performed to form corresponding factory area AGV demand mapping data, including: Based on the aforementioned material transportation demand change data, determine the change in material transportation demand within different plant areas; Based on the changes in material transportation demand within the corresponding areas of different factories, a planning analysis is conducted within the material transportation time limit to determine the minimum AGV demand for continuous operation. For different factory areas, the corresponding change in AGV supply is determined based on the minimum AGV demand and the current number of AGVs. The total supply change is determined based on the supply change of the AGVs in different factory areas.

8. The method according to claim 7, characterized in that, The method of performing collaborative analysis based on the shortest cross-regional scheduling path according to the AGV demand mapping data of different factory areas to form the cross-regional scheduling collaborative adjustment data includes: Confirm the scheduling path between any two factory areas and AGV supply stations to form cross-regional scheduling path data; Based on the changes in AGV supply in different factory areas and the total changes in supply at the overall scheduling point, cross-regional scheduling is quantified using the cross-regional scheduling path data to form cross-regional scheduling quantified data. Based on the cross-regional scheduling quantification data, a collaborative analysis based on the shortest cross-regional scheduling path is performed to form the cross-regional scheduling collaborative adjustment data.

9. The method according to claim 8, characterized in that, The process of quantifying cross-regional scheduling based on the supply changes of AGVs in different factory areas and the total supply changes at the overall scheduling point, combined with the cross-regional scheduling path data, forms cross-regional scheduling quantified data, including: Different factory areas are numerically calibrated based on the changes in AGV supply in the factory area, and the AGV supply stations are numerically calibrated based on the total changes in supply. Using the material delivery point in the factory area as the scheduling location point, and the entrance and exit locations of the AGV supply station as the scheduling location points, determine the scheduling path between any two of the scheduling location points, and for any two of the scheduling location points: The directional path from the scheduling location point with the larger calibrated value to the scheduling location point with the smaller calibrated value is determined as the cross-regional supplementary scheduling path. The directional path from the scheduling location point with the smaller calibrated value to the scheduling location point with the larger calibrated value is determined as the cross-regional reduction scheduling path. The cross-regional scheduling quantification data is formed by combining the calibration values ​​corresponding to different scheduling location points, the cross-regional supplementary scheduling paths, and the cross-regional reduction scheduling paths.

10. The method according to claim 9, characterized in that, The step of performing collaborative analysis based on the shortest cross-regional scheduling path according to the cross-regional scheduling quantification data to form the cross-regional scheduling collaborative adjustment data includes: The selection of the cross-regional supplementary scheduling path and the cross-regional reduction scheduling path is based on the calibration values ​​corresponding to different scheduling location points, and the selection specifications are as follows: For each cross-regional supplementary scheduling path selected at the corresponding scheduling location point, the calibrated value is decremented by one. For each cross-regional reduction scheduling path selected at the corresponding scheduling location point, the calibrated value is incremented by one. For any of the aforementioned scheduling locations, the following must be satisfied: The calibrated value is calculated based on the number of the selected associated cross-regional supplementary scheduling paths and the number of cross-regional reduction scheduling paths, so that the calculated value is zero. The combination with the shortest total distance among the different combinations of cross-regional supplementary scheduling paths and cross-regional reduction scheduling paths that meet the requirements, along with the corresponding supply quantity of the AGV supply station, is determined as the cross-regional scheduling collaborative adjustment data.

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