Multi-model cutting piece conveying scheduling method and system based on work hour system

Abstract

The application provides a kind of multi-vehicle type piece conveying scheduling method and system based on time system, belong to piece conveying scheduling technical field.The method includes: for the logistics transfer task, task identification information, material information, starting position, target position and task priority information are configured;Determine the target intelligent conveying equipment for executing the logistics transfer task;Through intelligent scheduling system, device control instructions containing moving path, material taking position and material placing position are generated;According to the change of transportation environment, the moving path is adjusted;Device state information and task execution state information are obtained;Through the target intelligent conveying equipment, the current task identification information, device position information and task execution progress information are saved to form breakpoint snapshot;Through intelligent scheduling system, task completion information is fed back to time management system.The application realizes linkage scheduling intelligent conveying equipment, dynamically plans path and supports abnormal recovery, improves piece logistics efficiency and reliability.

Description

Technical Field

[0001] This invention relates to the field of fabric piece transportation and scheduling technology, and specifically to a multi-vehicle fabric piece transportation and scheduling method and system based on a work hour system. Background Technology

[0002] With the development of intelligent manufacturing technology, the garment manufacturing industry is gradually transforming towards digital production processes and automated logistics distribution. During the cutting and production flow, different types of cut materials need to be transferred promptly between storage areas, cutting areas, and processing stations based on production orders, process schedules, and production line material requirements. The multi-vehicle cut material transportation scheduling method and system based on a time-based system is an intelligent logistics scheduling technology that manages cut material transportation tasks using production process data and combines multiple types of transportation equipment to achieve automated cut material delivery. By linking production tasks, logistics needs, and equipment operating status, it achieves collaborative control between the cut material transportation process and the manufacturing process, improving the automation level of logistics management on the production floor.

[0003] However, the following technical problems still exist in the existing fabricated material logistics and transportation process: First, the existing production management system and material transportation system are usually independent of each other. Production orders, working hours information, and production line material requirements are difficult to be converted into transportation tasks in a timely manner. This results in the fabricated material delivery process relying on manual scheduling, making it impossible to dynamically adjust transportation tasks according to changes in production status, which can easily lead to waiting at production workstations or untimely material supply. Second, due to the differences in size, shape, and weight of fabricated materials, different types of transportation equipment need to be used for adaptation. However, the existing transportation system is difficult to intelligently match according to task requirements and equipment status. At the same time, in the process of multi-equipment collaborative operation, the fixed path planning method is difficult to adapt to changes in complex production environments, which can easily lead to path conflicts and reduced transportation efficiency. Third, the existing intelligent transportation equipment usually only performs material handling tasks and lacks a data closed-loop mechanism with the production management system. It cannot provide real-time feedback on equipment operating status, material delivery status, and task completion status. When equipment malfunctions or tasks are interrupted during transportation, it is also difficult to quickly resume transportation tasks based on the existing execution progress, affecting production continuity. Summary of the Invention

[0004] The purpose of this invention is to provide a multi-vehicle pattern piece logistics transportation method and system based on a work time system, in order to solve the technical problems of insufficient coordination between production tasks and logistics distribution processes, insufficient scheduling and route planning capabilities of multi-vehicle intelligent transportation equipment, and insufficient status feedback and anomaly recovery capabilities in existing pattern piece logistics transportation.

[0005] To achieve the above objectives, this invention provides a multi-vehicle pattern piece transportation scheduling method based on a work hour system. The method includes: acquiring production order information, work hour information, inventory information, and production line material demand information through a work hour management system; generating a logistics transfer task based on the material transfer requirements during the pattern piece production process; configuring task identification information, material information, starting position, target position, and task priority information for the logistics transfer task; sending the logistics transfer task to an intelligent scheduling system; parsing the logistics transfer task to obtain the corresponding material attributes and transportation requirements; and determining the target intelligent transportation equipment to execute the logistics transfer task by combining the equipment model information, equipment load information, location information, and operating status information of each intelligent transportation equipment in the intelligent transportation equipment cluster; and generating equipment control instructions including a movement path, material picking position, and material placing position through the intelligent scheduling system based on the location status of the target intelligent transportation equipment and the target position in the logistics transfer task, and sending these instructions to the target intelligent transportation equipment. The system controls the target intelligent transport equipment to execute the piece transport task according to the equipment control instructions. During the transport process, the SLAM navigation module and visual perception module in the intelligent transport equipment collect transport environment information and adjust the movement path according to changes in the transport environment. The intelligent scheduling system obtains the equipment status information and task execution status information of the target intelligent transport equipment during the execution of the logistics transfer task, and feeds the status information back to the time management system, so that the time management system updates the material delivery status, production task status, and logistics time data. When the target intelligent transport equipment experiences an abnormal interruption during the execution of the logistics transfer task, the target intelligent transport equipment saves the current task identification information, equipment location information, and task execution progress information to form a breakpoint snapshot, and resumes the execution of the logistics transfer task based on the breakpoint snapshot. After the logistics transfer task is completed, the intelligent scheduling system feeds back the task completion information to the time management system, so that the time management system updates the inventory data, work order status, and logistics records, realizing closed-loop data management between the time management system, the intelligent scheduling system, and the intelligent transport equipment.

[0006] Optionally, generating a logistics transfer task includes: triggering the generation of a logistics task based on changes in production orders, inventory changes, production line material requirements, and warehousing and transfer requirements; configuring a unique task identifier for the generated logistics transfer task and verifying the task status through the task identifier; and sending the verified logistics transfer task to the intelligent scheduling system.

[0007] Optionally, the intelligent scheduling system analyzes logistics transfer tasks by: determining the corresponding transport vehicle type based on the cut piece size, material type, and transport weight in the logistics transfer task; matching a frame-type vehicle when the transported object is a small-sized cut piece; matching a tray-type vehicle when the transported object is a large-sized cut piece; matching a hanger-type vehicle when the transported object is a semi-finished garment; and matching the corresponding model of intelligent conveying equipment based on the transport vehicle type and load-bearing requirements.

[0008] Optionally, determining the target intelligent transport device for performing the logistics transfer task includes: acquiring the online status, current location, power status, load status, and current task status of each intelligent transport device in the intelligent transport device cluster; and determining the target intelligent transport device from the intelligent transport device cluster based on the priority of the logistics transfer task, the current location of the device, and the operating status of the device.

[0009] Optionally, the intelligent conveying device for controlling the target to perform the cut piece transportation task according to the device control command includes: receiving the device control command sent by the intelligent scheduling system; controlling the intelligent conveying device to move to the material picking position according to the device control command and completing the loading of the cut piece material; controlling the intelligent conveying device to move to the target position and completing the unloading of the cut piece material; and detecting the status of obstacles in the transportation area through the visual perception module during transportation.

[0010] Optionally, adjusting the movement path according to changes in the transportation environment includes: acquiring environmental information of the operating area of ​​the intelligent transport equipment through a SLAM navigation module, and constructing a spatial map containing production equipment, transport channels, and work areas; establishing a three-dimensional potential energy field model based on the spatial map, using the target location of the logistics transfer task as the target constraint area, and using the areas where production equipment, personnel areas, and other intelligent transport equipment are located as obstacle constraint areas; determining the movement direction of the intelligent transport equipment based on the three-dimensional potential energy field model, and adjusting the movement path in conjunction with the dynamic environmental information collected by the visual perception module.

[0011] Optionally, feeding back the status information to the time management system includes: summarizing the location status, operating status, and task execution status uploaded by the intelligent transportation equipment through the intelligent scheduling system; establishing a logistics task status record based on the task identification information; and sending the logistics task status record to the time management system so that the time management system updates the logistics time data based on the cut piece delivery time, task completion time, and process waiting time.

[0012] Optionally, the step of restoring the logistics transfer task execution based on the breakpoint snapshot includes: when the intelligent transport equipment experiences communication abnormalities, equipment failures, or stops running, saving the current task identification information, equipment location, and completed task steps to form a breakpoint snapshot; after the abnormality is recovered, verifying the current location of the intelligent transport equipment based on the breakpoint snapshot; confirming through the work hour management system that the corresponding logistics transfer task is still in a valid execution state and confirming that there is still a material demand at the target production location; and generating a task resumption execution instruction based on the verification result, so that the intelligent transport equipment continues to execute the remaining transportation tasks.

[0013] Optionally, the multi-model cut piece transportation scheduling method further includes: connecting the time management system with an external production management system through a communication interface; wherein the external production management system includes an Enterprise Resource Planning (ERP) system, a Manufacturing Execution System (MES) system, and a Warehouse Management System (WMS); and obtaining production order information, inventory information, and logistics task information through data interaction to achieve collaborative logistics management in the production process.

[0014] On the other hand, this invention provides a multi-vehicle pattern piece transportation scheduling system based on a work hour system. The multi-vehicle pattern piece transportation scheduling system includes a core command module of a work hour management system, a core intelligent scheduling module, and an intelligent transportation equipment execution module. The core command module of the work hour management system is used to acquire production order information, work hour information, inventory information, and production line material demand information; generate logistics transfer tasks based on pattern piece transportation needs; and manage the addition, editing, pausing, termination, and priority adjustment of logistics transfer tasks. Simultaneously, the core command module of the work hour management system is connected to the production line system and the warehousing business system to associate production work order information and inventory information, and to receive real-time feedback on equipment status from the intelligent transportation equipment. The system receives logistics transfer tasks, parses and breaks them down, and generates execution instructions adapted to single intelligent transport equipment, multiple intelligent transport equipment, or intelligent transport equipment of different vehicle frame types based on the type of cut piece, transportation requirements, and execution requirements. Simultaneously, it acquires the online status, current location, battery status, load status, and task execution status of the intelligent transport equipment, determines the target intelligent transport equipment based on the priority of the logistics transfer task, equipment operating status, and transportation distance, and generates corresponding scheduling instructions. The intelligent scheduling core module is also used to analyze factory environment information and the operation of intelligent transport equipment. The system performs path planning in real-time, adjusting the transport path by combining preset transport paths with real-time environmental perception data. It also analyzes and handles path conflicts, point occupancy, and operational deadlocks that occur when multiple intelligent transport devices operate simultaneously, enabling collaborative operation of multiple devices. The intelligent transport device execution module, communicatively connected to the intelligent scheduling core module, receives scheduling instructions and executes the piece transport task. This module includes an autonomous navigation unit, a visual obstacle avoidance unit, a precise docking unit, an automatic material handling unit, a status detection unit, an emergency braking unit, and a task recovery unit. The task recovery unit is used to respond to power outages, emergency stops, communication failures, malfunctions, or manual pauses in the intelligent transport device. When a task is interrupted, the current task status is saved, forming a task snapshot containing task information, equipment location information, transportation route information, and material information. Based on task segmentation marking information and a recovery verification mechanism, the task snapshot is read after the equipment resumes operation, and the remaining transportation tasks are continued from the point of interruption. The core command module of the time management system also includes a data visualization unit and an anomaly management unit. The data visualization unit is used to build a logistics operation status display interface to visualize the location status of intelligent transportation equipment, task completion rate, and logistics operation efficiency. The anomaly management unit is used to detect, warn, push information, and record the handling of anomalies during transportation, realizing closed-loop management of logistics task anomaly handling.Through data interaction between the core command module, intelligent scheduling core module, and intelligent transportation equipment execution module of the work hour management system, the entire process of fabricated material logistics task generation, intelligent equipment scheduling, transportation execution, status feedback, and anomaly recovery is achieved through coordinated control.

[0015] Through the above technical solution, this invention links the work hour management system with the intelligent scheduling system and intelligent transportation equipment, automatically generating cut piece logistics transfer tasks based on production order information, work hour information, inventory information, and production line material requirements. It also dynamically manages these tasks based on their execution status, achieving collaborative control between production tasks and cut piece logistics distribution processes. This reduces material delivery delays caused by manual scheduling and improves information synchronization between the production and logistics processes. Furthermore, by analyzing the cut piece type, size, and transportation requirements in the logistics transfer tasks, and intelligently matching them with the equipment model, load status, and operating location in the intelligent transportation equipment cluster, the invention utilizes SLAM navigation modules, visual perception modules, and three-dimensional... The potential energy field model plans and dynamically adjusts transportation routes, enabling multi-vehicle intelligent transport equipment to operate autonomously and efficiently in various cut piece transportation needs and complex production environments. This reduces equipment resource waste and path conflicts, and improves the flexibility and stability of the cut piece transportation process. By collecting the location, operation, and task execution status of the intelligent transport equipment in real time and feeding the relevant data back to the time management system, and by restoring tasks based on breakpoint snapshots in the event of transportation anomalies, the model achieves the goals of traceable logistics execution, feedback on production status, and rapid recovery of abnormal tasks. This improves the continuity and reliability of the cut piece logistics transportation process, and further enhances the level of automation management and production collaboration efficiency in the garment manufacturing process.

[0016] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart illustrating the multi-vehicle pattern fabrication transportation scheduling method based on a work hour system according to the present invention. Figure 1 ; Figure 2 This is a flowchart illustrating the multi-vehicle pattern fabrication transportation scheduling method based on a work hour system according to the present invention. Figure 2 . Detailed Implementation

[0018] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0019] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with the relevant provisions of national laws and regulations. In the embodiments of this application, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this application, and do not imply that the applicant has already used or necessarily used such solutions.

[0020] Please refer to Figure 1 and Figure 2 This invention provides a multi-vehicle pattern fabric transportation scheduling method based on a work hour system. The multi-vehicle pattern fabric transportation scheduling method may include: Step S100: Obtain production order information, working hours information, inventory information and production line material requirements information through the working hours management system. Generate logistics transfer tasks based on the material transfer requirements in the cutting process, and configure task identification information, material information, starting position, target position and task priority information for the logistics transfer tasks.

[0021] In this embodiment of the invention, generating a logistics transfer task may include: triggering the generation of a logistics task based on changes in production orders, changes in inventory, material requirements of the production line, and warehousing and transfer requirements; configuring a unique task identifier for the generated logistics transfer task and verifying the task status through the task identifier; and sending the verified logistics transfer task to the intelligent scheduling system.

[0022] In this embodiment of the invention, the work time management system serves as the data entry point for the logistics scheduling of cut piece production. It is used to associate production orders, production processes, and material distribution requirements, and to generate corresponding logistics transfer tasks based on real-time business changes during the production process.

[0023] Specifically, the time management system interacts with the production management system, warehouse management system, and production line business system to obtain production order information, process execution information, inventory information, and production line material requirement information. Production order information is used to determine the current production model, production batch, and corresponding cut piece requirements; time information is used to determine the execution cycle time of each production process and material delivery time requirements; inventory information is used to determine the current storage status of cut pieces; and production line material requirement information is used to determine the material delivery requirements for the target production location.

[0024] When changes in production orders, inventory, production line material requirements, or warehousing and transfer needs are detected, the time management system triggers the generation of logistics tasks based on the current production task status. When generating a logistics transfer task, corresponding task data is configured based on the information of the cut pieces to be transported. A logistics transfer task includes at least: task identification information; cut piece material information; material quantity information; starting position; target position; and task priority information. The task identification information is used to uniquely identify the logistics transfer task, enabling the subsequent intelligent scheduling system to manage task status, track execution, and provide completion feedback based on the task identification information.

[0025] Furthermore, after a logistics transfer task is generated, the time management system verifies the task status. This includes: determining if the current logistics task is being generated repeatedly; determining if there is still a material requirement at the target production location; and determining if the inventory quantity meets the transportation requirements. Once the task verification is successful, the time management system sends the logistics transfer task to the intelligent scheduling system, which then executes subsequent equipment scheduling based on the task requirements. Through this method, the logistics task generation process can be linked to production orders, inventory status, and production needs, achieving the goal of having production needs drive the generation of material delivery tasks.

[0026] Step S200: Send the logistics transfer task to the intelligent scheduling system. The intelligent scheduling system parses the logistics transfer task to obtain the material attributes and transportation requirements corresponding to the logistics transfer task. Combined with the equipment model information, equipment load information, location information and operating status information of each intelligent transportation equipment in the intelligent transportation equipment cluster, the target intelligent transportation equipment to perform the logistics transfer task is determined.

[0027] In this embodiment of the invention, the intelligent scheduling system is used to receive logistics transfer tasks generated by the work hour management system, and to parse, split and schedule the logistics transfer tasks according to the attributes of the cut materials, transportation requirements and the operating status of the intelligent transportation equipment.

[0028] Specifically, after receiving a logistics transfer task, the intelligent scheduling system first establishes a corresponding task record based on the task identification information, and then analyzes the material information, transportation location, and task priority within the logistics transfer task. The material attributes corresponding to the logistics transfer task include: cut piece size information; cut piece type information; material weight information; and transportation quantity information. Transportation requirements include: starting transportation location; target delivery location; transportation distance; delivery time requirements; and task priority requirements. By analyzing the above information, the intelligent scheduling system can determine the transportation conditions corresponding to the current logistics task and select suitable intelligent transportation equipment to execute the transportation task.

[0029] In this embodiment of the invention, the intelligent scheduling system for analyzing logistics transfer tasks may include: determining the corresponding transport vehicle type based on the cut piece size, material type, and transport weight in the logistics transfer task; matching a frame-type vehicle when the transported object is a small-sized cut piece; matching a tray-type vehicle when the transported object is a large-sized cut piece; matching a hanger-type vehicle when the transported object is a semi-finished garment; and matching the corresponding model of intelligent transport equipment based on the transport vehicle type and load-bearing requirements.

[0030] Because the types, sizes, and transportation methods of cut pieces involved in the production of different vehicle models vary, the intelligent scheduling system matches transport vehicles based on the attributes of the cut pieces. Specifically, frame-type vehicles are used to carry smaller, more numerous cut pieces; tray-type vehicles are used to carry larger cut pieces or those requiring flat transport; and hanger-type vehicles are used to carry semi-finished garments that require hanging. The intelligent scheduling system performs adaptation analysis on intelligent transport equipment based on the type of transport vehicle and carrying requirements to determine the type of equipment that meets the current transportation needs. Through this method, cut pieces of different vehicle models and specifications within the same production area can be transported by corresponding types of intelligent transport equipment, improving the adaptability of logistics scheduling in multi-vehicle production scenarios.

[0031] In this embodiment of the invention, the intelligent scheduling system generates device matching conditions based on the parsing results and performs status analysis on the intelligent transportation device cluster. Each intelligent transportation device in the cluster has corresponding device status information. This device status information includes: device model information; online status information; current location information; battery status information; load status information; and current task status information.

[0032] The intelligent scheduling system acquires the real-time operating status of each device in the intelligent transportation equipment cluster and filters candidate devices that meet the current logistics transfer task requirements. Specifically, this includes: determining whether the intelligent transportation equipment supports the current transport vehicle based on its model information; determining whether the equipment's remaining carrying capacity meets the transportation requirements based on its load information; determining the distance of the equipment from the material picking location based on its location information; and determining whether the equipment has the capability to execute new tasks based on its task status. Through the above analysis, intelligent transportation equipment that cannot meet the transportation conditions is excluded.

[0033] In this embodiment of the invention, determining the target intelligent transportation device for performing the logistics transfer task may include: acquiring the online status, current location, power status, load status, and current task status of each intelligent transportation device in the intelligent transportation device cluster; and determining the target intelligent transportation device from the intelligent transportation device cluster based on the priority of the logistics transfer task, the current location of the device, and the device's operating status.

[0034] Specifically, the intelligent scheduling system sets equipment selection strategies based on the priority of logistics tasks. When multiple intelligent conveying devices meet the transportation requirements, a comprehensive matching is performed based on the device's current location, current workload, and operating status. For example, for high-priority logistics tasks, intelligent conveying devices that are closer to the picking location and currently idle are selected first; for ordinary logistics tasks, scheduling is based on the device's load and subsequent task arrangements. Through this method, the intelligent scheduling system can dynamically select execution devices based on real-time device status, avoiding the problem of reduced equipment resource utilization caused by fixed devices performing fixed tasks.

[0035] In this embodiment of the invention, the intelligent scheduling system can also perform collaborative scheduling based on the operational status of multiple logistics transfer tasks and multiple intelligent transport devices. Specifically, when multiple logistics transfer tasks exist simultaneously, the intelligent scheduling system adjusts the task execution order according to task priority, target location, and equipment operating status. Simultaneously, it analyzes and processes path conflicts, location occupancy, and operational deadlocks that occur during the simultaneous operation of multiple intelligent transport devices. For example, when multiple intelligent transport devices pass through the same transport area simultaneously, the intelligent scheduling system adjusts the device operating order based on task priority and the current location of the devices; when equipment is occupied in a transport area, the intelligent scheduling system controls subsequent devices to wait or adjusts local transport paths; when potential operational conflicts between devices are detected, the system adjusts the device operating strategy in advance. Through this multi-device collaborative scheduling mechanism, multiple intelligent transport devices can maintain orderly operation within the same production area.

[0036] In this embodiment of the invention, the intelligent scheduling system can also split tasks for a single intelligent transport device, multiple intelligent transport devices, and intelligent transport devices with different vehicle-mounted frame types according to the execution requirements of logistics tasks. Specifically, when the logistics transfer task corresponds to a small quantity of materials and a short transportation distance, a single device execution instruction is generated; when the logistics transfer task corresponds to a large quantity of materials or has multiple delivery locations, the task is split into multiple sub-tasks and assigned to multiple intelligent transport devices; when different types of cut pieces have transportation needs at the same time, corresponding device execution instructions are generated according to the vehicle type. Through task parsing, device matching, and intelligent allocation processes, the intelligent scheduling system can adapt to multi-vehicle, multi-batch, and multi-task parallel production environments.

[0037] Step S300: Based on the location status of the target intelligent conveying equipment and the target location in the logistics transfer task, generate equipment control instructions containing the movement path, material picking location, and material unloading location through the intelligent scheduling system, and send them to the target intelligent conveying equipment.

[0038] In this embodiment of the invention, after the intelligent scheduling system determines the target intelligent transport equipment to perform the logistics transfer task, it generates corresponding equipment control instructions based on the current location of the target intelligent transport equipment, the material pick-up location, and the target production location. These equipment control instructions, used to control the target intelligent transport equipment to complete the material transport process, include at least: task identification information; target intelligent transport equipment information; movement path information; material pick-up location information; material release location information; and execution action sequence information.

[0039] Specifically, the intelligent scheduling system determines the material picking area based on the starting position of the logistics transfer task, the material delivery area based on the target location, and generates the equipment movement path based on the current location of the target intelligent conveyor equipment. During the movement path generation process, the intelligent scheduling system comprehensively considers: the current location of the intelligent conveyor equipment; the status of the factory's transportation channels; the distribution of production areas; task priority requirements; and the operating status of other intelligent conveyor equipment. By analyzing the above information, the system determines the transportation path for the target intelligent conveyor equipment to move from its current location to the picking location, and then from the picking location to the target unloading location.

[0040] In this embodiment of the invention, the intelligent scheduling system generates a corresponding action control sequence based on the material transportation process. Specifically, this includes: first, controlling the target intelligent conveying equipment to move to the material picking position; second, generating a material loading instruction based on automatic material picking and unloading requirements; then, controlling the target intelligent conveying equipment to move to the target production position along the planned path; and finally, generating a material unloading instruction to complete the material delivery. By associating the movement path, picking action, and unloading action, the equipment control instructions can correspond to the complete logistics transportation process.

[0041] Furthermore, after generating equipment control commands, the intelligent scheduling system performs task association verification on the commands. Specifically, based on the task identification information, it determines: whether the current equipment control command corresponds to a valid logistics transfer task; whether the target intelligent transport equipment is in an executable state; and whether there is still a need for cut piece delivery at the target location. If the verification passes, the equipment control command is sent to the target intelligent transport equipment. If a change in task status is detected, such as the target production location canceling material requirements or the target equipment malfunctioning, the intelligent scheduling system readjusts the equipment control commands.

[0042] In this embodiment of the invention, the intelligent scheduling system can also dynamically adjust equipment control commands based on feedback information during equipment operation. For example, when the target intelligent conveying equipment has not yet started its transport task, the system reselects the execution equipment based on changes in equipment status; when the target intelligent conveying equipment detects a path change during transport, the system adjusts the movement path based on real-time environmental information; and when the target production location changes, the system regenerates the material unloading location. Through this dynamic control mechanism, equipment control commands can adapt to changes in the production site.

[0043] Step S400: Control the target intelligent transport equipment to execute the cut piece transport task according to the equipment control instructions. During the transport process, the SLAM navigation module and visual perception module in the intelligent transport equipment collect transport environment information and adjust the movement path according to changes in the transport environment.

[0044] In this embodiment of the invention, after receiving the equipment control command sent by the intelligent scheduling system, the target intelligent conveying equipment executes the cut material transportation task according to the task identification information, movement path information, material picking location information, and material placement location information in the equipment control command. The intelligent conveying equipment includes: an autonomous navigation unit; a visual perception unit; a precise docking unit; an automatic material picking and placing unit; a status detection unit; and an emergency braking unit. Through data interaction between the above functional units, the intelligent conveying equipment can complete the automatic picking, autonomous transportation, and precise delivery of cut materials.

[0045] In this embodiment of the invention, controlling the target intelligent conveying device to execute the cut piece transportation task according to the device control command may include: First, the target intelligent conveying device receives the device control command sent by the intelligent scheduling system, parses the device control command, and obtains the execution information corresponding to the current logistics transfer task. Then, the target intelligent conveying device controls the movement mechanism to operate according to the material picking position, and moves to the location of the cut piece material through the autonomous navigation unit. When the intelligent conveying device arrives at the picking area, it adjusts its current position through the precise docking unit to match the device docking position with the cut piece material loading position. Then, the automatic material picking and unloading unit completes the loading of the cut piece material. After loading is completed, the intelligent conveying device moves to the target production position according to the movement path information in the device control command and performs the cut piece material unloading action.

[0046] In this embodiment of the invention, the intelligent transport equipment achieves autonomous movement control during the transport process through an autonomous navigation unit. Specifically, the autonomous navigation unit controls the intelligent transport equipment to run along the planned path based on the movement path information generated by the intelligent scheduling system. During operation, the autonomous navigation unit acquires in real time: the current position of the intelligent transport equipment; the current direction of movement; the distance to the target position; and the path execution status. It then matches the actual operating status of the equipment with the planned path. When the equipment's trajectory deviates from the preset path, the movement direction is adjusted according to the relationship between the current position and the target position, allowing the intelligent transport equipment to re-enter the target transport path. Through the autonomous navigation process, the intelligent transport equipment can complete the transport of cut pieces within the factory area without manual operation.

[0047] In this embodiment of the invention, the intelligent transport equipment collects environmental information of the operating area through a SLAM navigation module during transportation and constructs a transport space map based on this information. The environmental information collected by the SLAM navigation module includes: production equipment location information; factory transport channel information; work area information; and fixed obstacle information. The intelligent transport equipment determines its own spatial location based on the collected environmental information and establishes a corresponding transport environment map.

[0048] Furthermore, when the production environment changes, the SLAM navigation module updates the spatial map based on real-time collected information. For example, when new equipment is added to the production area or the status of transport channels changes, the intelligent transport equipment can replan its operating path based on the updated spatial map. Through the SLAM navigation mechanism, the intelligent transport equipment can adapt to changes in production layout in multi-model production environments.

[0049] In this embodiment of the invention, the intelligent conveying equipment acquires dynamic environmental information in the transport area in real time through a visual perception module. The visual perception module detects: personnel movement; the operating status of other intelligent conveying equipment; temporarily stored materials; and lane occupancy. When the visual perception module detects an obstacle in the transport path, it sends the obstacle information to the intelligent conveying equipment control module. The control module determines the handling method based on the obstacle's location and the current transport status, specifically including: maintaining the original path when the obstacle does not affect the current transport path; reducing the equipment's operating speed when the obstacle enters a safe range; and adjusting the movement path or performing temporary avoidance when the obstacle blocks the transport path. By combining visual perception with autonomous navigation, the operational safety of the intelligent conveying equipment in complex production environments is improved.

[0050] In this embodiment of the invention, the intelligent transport equipment dynamically adjusts its transport path based on the spatial map established by the SLAM navigation module and the dynamic environmental information acquired by the visual perception module. Specifically, the intelligent scheduling system pre-generates a basic transport path, and the intelligent transport equipment optimizes the path during execution based on the real-time environmental conditions. The target production location is used as the target area for path optimization, while production equipment, personnel areas, and areas where other intelligent transport equipment is located are designated as restricted areas. The equipment's movement direction is analyzed based on the current environmental information, and local transport paths are adjusted accordingly. For example, when personnel are present on the original transport path, the intelligent transport equipment avoids areas where personnel are active; when a transport channel is occupied by other equipment, the intelligent transport equipment selects an alternative transport path; when the layout of the production area changes, the movement direction is replanned based on the updated environmental map. Through dynamic path optimization, the intelligent transport equipment can adapt to real-time changes in the production site.

[0051] In this embodiment of the invention, when the intelligent conveying equipment reaches the material picking position or the target material placement position, the equipment position is adjusted by a precise docking unit. Specifically, the precise docking unit adjusts the position of the intelligent conveying equipment based on: the current equipment coordinates; the target docking position; and the equipment posture information, to meet the material picking and placement requirements. After precise docking, the automatic picking and placing unit executes corresponding actions according to the equipment control instructions. During the picking phase: the intelligent conveying equipment controls the carrier to approach the material piece; detects the loading status of the material piece; and secures the material. During the placement phase: the intelligent conveying equipment moves to the target production position; confirms the unloading area; and releases the material piece. Through the automatic picking and placing mechanism, manual intervention is reduced, and the automation level of material piece logistics transportation is improved.

[0052] In this embodiment of the invention, the intelligent transportation equipment acquires its operating status in real time through a status detection unit during the execution of a transportation task. The detected status includes: equipment operating status; battery status; load status; communication status; and fault status. When an abnormality is detected, corresponding processing is performed based on the anomaly. For example, when a equipment malfunction is detected, the current transportation action is stopped and the abnormality information is reported to the intelligent scheduling system; when a safety risk is detected, the equipment operation is stopped via an emergency braking unit; and when the equipment returns to normal, the transportation task continues according to the task recovery mechanism.

[0053] In this embodiment of the invention, adjusting the movement path according to changes in the transportation environment may include: obtaining environmental information of the operating area of ​​the intelligent transport equipment through a SLAM navigation module, and constructing a spatial map containing production equipment, transportation channels, and work areas; establishing a three-dimensional potential energy field model based on the spatial map, taking the target location of the logistics transfer task as the target constraint area, and taking the areas where production equipment, personnel areas, and other intelligent transport equipment are located as obstacle constraint areas; determining the movement direction of the intelligent transport equipment according to the three-dimensional potential energy field model, and adjusting the movement path in conjunction with the dynamic environmental information collected by the visual perception module.

[0054] Step S500: Obtain the equipment status information and task execution status information of the target intelligent transportation equipment during the logistics transfer process through the intelligent scheduling system, and feed the status information back to the time management system so that the time management system can update the material delivery status, production task status and logistics time data.

[0055] In this embodiment of the invention, the intelligent scheduling system collects real-time data on the operating status of the intelligent conveying equipment and the execution status of the logistics task during the execution of the cut piece transportation task by the target intelligent conveying equipment, and feeds the collected data back to the time management system. The equipment status information acquired by the intelligent scheduling system includes: the current location of the intelligent conveying equipment; online operating status; power status; load status; communication status; and fault status. The task execution status information includes: logistics task identification information; current execution stage; task completion progress; transportation route execution status; material handling status; and abnormal status information. By collecting the above data in real time, the time management system can grasp the entire status of the cut piece logistics transportation process.

[0056] In this embodiment of the invention, feeding back status information to the time management system may include: summarizing the location status, operating status, and task execution status uploaded by the intelligent transportation equipment through the intelligent scheduling system; establishing a logistics task status record based on the task identification information; and sending the logistics task status record to the time management system so that the time management system updates the logistics time data based on the cut piece delivery time, task completion time, and process waiting time.

[0057] Specifically, after receiving data from the intelligent transportation equipment, the intelligent scheduling system processes data from different sources in a unified manner. This includes establishing corresponding task status records based on logistics task identification information, which are used to link: logistics task generation time; equipment response time; transportation execution time; and task completion time. Through these task status records, each piece of fabric transportation task has complete data tracking information.

[0058] In this embodiment of the invention, the time management system monitors the status of cut piece delivery in real time based on data fed back from the intelligent scheduling system. Specifically, the time management system displays the current execution status of logistics tasks based on the logistics task status records. The monitored content includes: the currently executing device; The system monitors equipment location; transportation route status; cut piece delivery progress; and task completion status. Simultaneously, the core command module of the time management system supports adding, editing, pausing, terminating, and prioritizing logistics tasks. When production tasks change, managers can adjust corresponding logistics tasks through the time management system, and the intelligent scheduling system will then reassign tasks. Through logistics status monitoring, transparent management of the logistics process on the production floor is achieved.

[0059] In this embodiment of the invention, the time management system updates logistics time information based on time data during the execution of logistics tasks. Specifically, this includes: the start time of cut piece delivery; the response time of intelligent conveying equipment; equipment transportation time; material loading time; material unloading time; and task completion time. The time management system generates an actual execution record of the logistics task based on the above data and associates it with production process information. For example, when the delivery time of cut pieces for a certain vehicle model exceeds the preset production cycle time requirement, the time management system can analyze the reasons for the waiting based on the logistics task record. If the reason is due to equipment scheduling, the intelligent conveying equipment allocation strategy is optimized; if the reason is due to the transportation path, the path planning strategy is adjusted; if the reason is due to changes in material requirements, the task priority is readjusted. Through updating logistics time data, the production management process can be optimized based on the actual logistics status.

[0060] In this embodiment of the invention, the time management system can also be connected to the production line system and the warehousing business system to achieve linkage between logistics data and production business data. Specifically, the time management system updates the production task status based on the fabric piece delivery status. For example, when the corresponding fabric piece for the production line has not yet been delivered, the corresponding work order status is kept in the "waiting for materials" state; when the fabric piece is delivered and arrives at the target production location, the corresponding work order status is updated to the "ready to produce" state. At the same time, the time management system updates the material inventory status based on inventory information and the results of logistics task execution. Through the linkage of production business, warehousing, logistics, and production processes are coordinated and managed.

[0061] In this embodiment of the invention, the core command module of the time management system also includes a data visualization unit for visually displaying the status of logistics operations. Specifically, the data visualization unit constructs a logistics operation status display interface based on data fed back from the intelligent scheduling system. The displayed content includes: the location status of intelligent transport equipment; the current number of tasks; the task completion rate; the equipment operating status; and the logistics operation efficiency. Simultaneously, the intelligent transport equipment can be configured with a visualization display unit to display the currently executing tasks, operating status, and abnormal prompts in real time. Through data visualization management, production managers can intuitively grasp the logistics operation status of the factory area.

[0062] In this embodiment of the invention, the time management system further includes an anomaly management unit for managing abnormal states during logistics transportation. Specifically, when the intelligent scheduling system detects an abnormal state in the intelligent transportation equipment, it feeds back the anomaly information to the time management system. The anomaly information includes: equipment malfunction information; task interruption information; communication anomaly information; and transportation anomaly information. Based on the anomaly information, the time management system performs: anomaly warning; information push; anomaly recording; and handling tracking. It also associates the anomaly handling results with the corresponding logistics task, achieving full-process recording of anomaly issues.

[0063] Step S600: When an abnormal interruption occurs during the execution of a logistics transfer task by the target intelligent transportation device, the current task identification information, device location information, and task execution progress information are saved by the target intelligent transportation device to form a breakpoint snapshot, and the execution of the logistics transfer task is resumed based on the breakpoint snapshot.

[0064] In this embodiment of the invention, the intelligent transport device continuously monitors its operating status through a status detection unit during the execution of the cut piece transport task. When an abnormal interruption is detected, the intelligent transport device does not immediately clear the currently executing task, but instead saves the current logistics transfer task status, forming a snapshot of the corresponding breakpoint, so that the unfinished task can continue to be executed after the device recovers. Abnormal interruption situations include: power failure; emergency stop operation; communication connection interruption; equipment malfunction shutdown; and manual pause operation. Through the abnormal status detection mechanism, the intelligent transport device can save the task execution status for different interruption situations, avoiding the regeneration or repeated transport of logistics tasks due to task interruption.

[0065] In this embodiment of the invention, when the intelligent delivery device detects an abnormal interruption in a logistics transfer task, it first obtains the current task execution status and generates a breakpoint snapshot. The breakpoint snapshot includes at least: current task identification information; intelligent delivery device identification information; current device location information; current transportation path information; current task execution progress information; and cut material information. Specifically, the task identification information is used to associate with the current logistics transfer task; the device location information is used to determine the device's location when the task was interrupted; the transportation path information is used to record the path nodes already executed by the device and the unfinished paths; and the task execution progress information is used to identify the current stage of the task. For example, when the intelligent delivery device experiences a communication failure during transportation, the system records that the device has completed the material picking action and saves the current transportation location and the remaining transportation path; when the device restores communication, the remaining transportation process can continue based on the breakpoint snapshot.

[0066] In this embodiment of the invention, to improve the accuracy of anomaly recovery, the intelligent conveying equipment divides the task execution process into stages and establishes task segment markers during the execution of logistics transfer tasks. Specifically, the cut piece transportation task is divided into: material picking stage; loading confirmation stage; transportation stage; route adjustment stage; unloading stage; and task completion confirmation stage. The intelligent conveying equipment records the corresponding task stage identifier according to the current execution status. When an anomaly occurs, the completed task steps and the task steps to be executed are determined according to the task segment markers. For example, if the equipment encounters an anomaly after completing the loading of cut pieces, there is no need to re-execute the material picking action during recovery; if the equipment encounters an anomaly during transportation, it can directly continue moving from the current transportation position to the target position during recovery. Through the task segmentation marker mechanism, repetitive operations during the task recovery process are reduced, and the efficiency of anomaly recovery is improved.

[0067] In this embodiment of the invention, the intelligent delivery device caches its own positioning coordinates in real time during the execution of a transportation task. When the device experiences an abnormal interruption, it performs a recovery verification of the device's current position based on the device location information saved in the breakpoint snapshot and the cached positioning coordinate information. Specifically, this includes: after abnormal recovery, obtaining the current spatial position of the intelligent delivery device; reading the device interruption position in the breakpoint snapshot; and comparing whether the current device position matches the interruption position. When the current position meets the recovery conditions, the device positioning is determined to be valid; when a device position offset is detected, environmental positioning is re-performed through the SLAM navigation module. This positioning verification mechanism prevents incorrect position recovery due to device movement offset or environmental changes.

[0068] In this embodiment of the invention, before resuming the execution of the logistics transfer task, the intelligent scheduling system and the time management system jointly confirm the task status. Specifically: the intelligent scheduling system reads the task identification information from the breakpoint snapshot; the time management system queries the status of the corresponding logistics task; determines whether the current task is still in a valid execution state; and confirms whether there is still a cutting demand at the target production location. If it is detected that: the logistics task has been canceled; the production demand has changed; or the target location does not require delivery, then the resumption of execution is stopped, and a new logistics scheduling task is generated. If it is confirmed that the logistics task is still valid, then a task resumption execution instruction is generated.

[0069] In this embodiment of the invention, when the equipment status returns to normal and the task verification passes, the intelligent scheduling system generates a resumption execution instruction based on the breakpoint snapshot. The resumption execution instruction includes: the remaining movement path; the stage of the task to be completed; the target location; and the remaining material handling actions. After receiving the resumption execution instruction, the target intelligent transportation equipment continues to execute the remaining transportation task according to the saved task status. Specifically, if the equipment has not yet completed transportation, it continues to execute the remaining movement path; if the equipment has reached the target location but has not completed unloading, it continues to execute the unloading action; if the equipment has completed material delivery, it reports the task completion status. Through the breakpoint resume mechanism, the logistics task is not interrupted in abnormal situations, and there is no need to reissue the complete task.

[0070] In this embodiment of the invention, after the intelligent delivery equipment resumes task execution, it feeds back the recovery result to the intelligent scheduling system. The intelligent scheduling system updates the logistics task status based on the feedback information and synchronizes it to the time management system. The synchronized information includes: task recovery time; anomaly occurrence time; anomaly type; recovery execution status; and task completion status. The time management system updates the logistics records based on the above data, enabling full tracking of the anomaly occurrence, handling, and recovery process.

[0071] In this embodiment of the invention, restoring the execution of a logistics transfer task based on a breakpoint snapshot may include: when the intelligent transport equipment experiences a communication anomaly, equipment failure, or stops running, saving the current task identification information, equipment location, and completed task steps to form a breakpoint snapshot; after the anomaly is recovered, verifying the current location of the intelligent transport equipment based on the breakpoint snapshot; confirming through the work hour management system that the corresponding logistics transfer task is still in a valid execution state and confirming that there is still a material demand at the target production location; and generating a task resumption execution instruction based on the verification result, enabling the intelligent transport equipment to continue executing the remaining transport tasks.

[0072] Step S700: After the logistics transfer task is completed, the intelligent scheduling system feeds back the task completion information to the time management system, so that the time management system updates the inventory data, work order status and logistics records, thereby realizing closed-loop data management between the time management system, the intelligent scheduling system and the intelligent transportation equipment.

[0073] In this embodiment of the invention, after the target intelligent conveying equipment completes the fabric piece transportation task, the intelligent scheduling system confirms the execution result of the logistics transfer task and feeds back the task completion information to the time management system. The task completion information includes: logistics task identification information; intelligent conveying equipment information; fabric piece material information; actual transportation route information; task completion time; exception handling record; and task execution result. Based on the status information fed back by the intelligent conveying equipment, the intelligent scheduling system makes a comprehensive judgment on the fabric piece picking, transportation, and unloading processes.

[0074] Specifically, once the intelligent conveying equipment has stopped at the target location and unloaded the cut materials, the automatic material handling unit reports the material release status. Simultaneously, the system combines this information with the task execution status to determine whether the current logistics transfer task is complete. Upon confirmation of task completion, the intelligent scheduling system updates the logistics task status and sends the task completion information to the time management system.

[0075] In this embodiment of the invention, after receiving task completion information, the time management system associates the corresponding cut material information with the logistics task identifier information and updates the inventory data. Specifically, when cut materials are retrieved from the storage area, the time management system updates the warehouse inventory status according to the logistics task execution status; when cut materials are delivered to the target production location, the system updates the material status at the production site according to the actual delivery results. Simultaneously, the time management system can interact with the warehouse management system (WMS) via a communication interface to achieve synchronous updates of warehouse inventory information. Through dynamic updates of inventory status, the warehouse system can monitor the flow of cut materials in real time, providing a data foundation for the generation of subsequent logistics tasks.

[0076] In this embodiment of the invention, the time management system synchronously adjusts the production work order status based on the completion status of cut piece delivery. Specifically, when the target production location has not received the corresponding cut piece, the production work order remains in a material waiting state; once the cut piece delivery is completed, the corresponding production work order is updated to an executable state. Simultaneously, the time management system performs correlation analysis on material delivery time and process waiting time during the production process based on logistics task execution records. By synchronizing the production work order status, the logistics delivery process is kept consistent with the manufacturing process, achieving collaborative management of production tasks and logistics tasks.

[0077] In this embodiment of the invention, the multi-model cut piece transportation scheduling method may further include: connecting the work hour management system with an external production management system through a communication interface; wherein, the external production management system includes an enterprise resource planning system (ERP), a manufacturing execution system (MES), and a warehouse management system (WMS); and obtaining production order information, inventory information, and logistics task information through data interaction to achieve collaborative logistics management in the production and manufacturing process.

[0078] Specifically, the ERP system provides production orders and resource management information; the MES system links production task execution status; and the WMS system manages cut piece inventory and warehousing and transportation status. Through data interaction between multiple systems, production orders, material inventory, logistics and transportation, and production execution status are formed into a unified data chain.

[0079] In this embodiment of the invention, closed-loop management of the entire process of fabricated piece logistics is achieved through data interaction between the time management system, the intelligent scheduling system, and the intelligent conveying equipment. The specific process is as follows: First, the time management system generates a logistics transfer task based on production order information, time information, inventory information, and production line material demand information, and sends it to the intelligent scheduling system. Second, the intelligent scheduling system parses the logistics transfer task, determines the target intelligent conveying equipment based on the fabricated piece type, transportation requirements, and equipment status, and generates equipment control instructions. Third, the intelligent conveying equipment executes the fabricated piece transportation task according to the equipment control instructions, and provides real-time feedback on equipment status and task execution status. Then, the intelligent scheduling system summarizes and processes the feedback data and sends the task execution results back to the time management system. Finally, the time management system updates inventory data, production work order status, and logistics records based on task completion information. Through the above process, the following is achieved: production demand generates logistics tasks; logistics tasks drive equipment execution; equipment execution provides feedback on business status; and business status optimizes production management.

[0080] In this embodiment of the invention, because the time management system continuously records task data, equipment status data, and anomaly handling data during the execution of logistics tasks, it can optimize the subsequent logistics scheduling process based on historical logistics data. Specifically, it analyzes historical task execution records to determine: the utilization of intelligent transport equipment; the efficiency of fabric transport for different vehicle models; the execution time of logistics tasks; and the frequency of anomalies. Based on the analysis results, it adjusts the priority of subsequent logistics tasks, equipment allocation strategies, and transportation route planning methods. Through closed-loop data management, the system can continuously optimize logistics scheduling strategies according to the actual production process, improving the adaptability of fabric transport in multi-vehicle production environments.

[0081] On the other hand, the present invention also provides a multi-vehicle pattern piece transportation scheduling system based on a work hour system, the multi-vehicle pattern piece transportation scheduling system including a work hour management system core command module, an intelligent scheduling core module, and an intelligent transportation equipment execution module.

[0082] The core command module of the time management system can acquire production order information, time information, inventory information, and production line material demand information. It generates logistics transfer tasks based on the needs of fabricated piece transportation and manages the addition, editing, pausing, termination, and priority adjustment of these tasks. Simultaneously, the core command module connects with the production line system and the warehousing business system to associate production work order information and inventory information, and receives real-time feedback from intelligent transportation equipment on equipment status, task execution status, and logistics completion information.

[0083] The intelligent scheduling core module is communicatively connected to the core command module of the work hour management system. It is used to receive logistics transfer tasks, parse and break down the logistics transfer tasks, and generate execution instructions adapted to a single intelligent transport device, multiple intelligent transport devices, or intelligent transport devices with different vehicle frame types according to the type of cut pieces, transportation requirements, and execution requirements. At the same time, it obtains the online status, current location, power status, load status, and task execution status of the intelligent transport devices, determines the target intelligent transport device according to the priority of the logistics transfer task, the operating status of the equipment, and the transportation distance, and generates corresponding scheduling instructions.

[0084] The intelligent scheduling core module can also be used to plan routes based on the factory environment information and the operating status of intelligent transportation equipment. It can adjust the transportation route by combining the preset transportation route with real-time environmental perception data, and analyze and process the path conflicts, point occupancy and operation deadlock that occur when multiple intelligent transportation equipment are running at the same time, so as to realize the collaborative operation of multiple equipment.

[0085] The intelligent conveying equipment execution module is communicatively connected to the intelligent scheduling core module, and is used to receive scheduling instructions and execute the cutting piece transportation task. The intelligent conveying equipment execution module includes an autonomous navigation unit, a visual obstacle avoidance unit, a precise docking unit, an automatic material picking and placing unit, a status detection unit, an emergency braking unit, and a task recovery unit.

[0086] The task recovery unit can be used to save the status of the currently executing task when the intelligent transportation equipment experiences a power outage, emergency stop, communication disconnection, fault shutdown, or manual pause that causes the task to be interrupted. This will form a task snapshot containing task information, equipment location information, transportation path information, and material information. Based on the task segmentation marking information and the recovery verification mechanism, the task snapshot can be read after the equipment resumes operation, and the remaining transportation tasks can be continued from the point of task interruption.

[0087] The core command module of the work hour management system may also include a data visualization unit and an anomaly management unit. The data visualization unit is used to build a logistics operation status display interface to visualize the location status of intelligent transportation equipment, task completion rate, and logistics operation efficiency. The anomaly management unit is used to detect, warn, push information, and record the handling of abnormal states during transportation, so as to realize closed-loop management of logistics task anomaly handling.

[0088] Through data interaction between the core command module, intelligent scheduling core module, and intelligent transportation equipment execution module of the time management system, the entire process of fabrication logistics task generation, intelligent equipment scheduling, transportation execution, status feedback, and anomaly recovery is achieved through collaborative control.

[0089] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0090] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0091] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0092] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0093] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0094] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0095] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0096] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0097] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A multi-vehicle-type cut piece transportation scheduling method based on a work-hour system, characterized in that, The multi-vehicle cut piece transportation and scheduling method includes: The system obtains production order information, working hour information, inventory information and production line material demand information through the working hour management system. Based on the material transfer requirements in the cutting process, it generates logistics transfer tasks and configures task identification information, material information, starting position, target position and task priority information for the logistics transfer tasks. The logistics transfer task is sent to the intelligent scheduling system. The intelligent scheduling system parses the logistics transfer task to obtain the material attributes and transportation requirements corresponding to the logistics transfer task. Combined with the equipment model information, equipment load information, location information and operating status information of each intelligent transportation equipment in the intelligent transportation equipment cluster, the target intelligent transportation equipment to execute the logistics transfer task is determined. Based on the location status of the target intelligent transport equipment and the target location in the logistics transfer task, the intelligent scheduling system generates equipment control instructions containing the movement path, material picking location, and material unloading location, and sends them to the target intelligent transport equipment. The intelligent transport equipment controls the target to execute the piece transport task according to the equipment control instructions. During the transport process, the SLAM navigation module and visual perception module in the intelligent transport equipment collect transport environment information and adjust the movement path according to changes in the transport environment. The intelligent scheduling system obtains the equipment status information and task execution status information of the target intelligent transportation equipment during the logistics transfer process, and feeds the status information back to the time management system, so that the time management system can update the material distribution status, production task status and logistics time data. When an abnormal interruption occurs during the execution of a logistics transfer task by the target intelligent transportation device, the current task identification information, device location information, and task execution progress information are saved by the target intelligent transportation device to form a breakpoint snapshot, and the execution of the logistics transfer task is resumed based on the breakpoint snapshot; After the logistics transfer task is completed, the intelligent scheduling system feeds back the task completion information to the time management system, which then updates the inventory data, work order status and logistics records, thus achieving closed-loop data management between the time management system, the intelligent scheduling system and the intelligent transportation equipment.

2. The multi-vehicle pattern piece transportation scheduling method based on a work hour system according to claim 1, characterized in that, The generated logistics transfer task includes: Logistics tasks are generated based on changes in production orders, inventory changes, production line material requirements, and warehousing and transshipment needs. Configure a unique task identifier for each generated logistics transfer task, and verify the task status using the task identifier. The verified logistics transfer task is sent to the intelligent scheduling system.

3. The multi-vehicle pattern piece transportation scheduling method based on a work hour system according to claim 1, characterized in that, The intelligent scheduling system analyzes logistics transfer tasks, including: The type of transport vehicle is determined based on the cut piece size, material type, and transport weight in the logistics transfer task. When transporting small-sized cut pieces, use a frame-type carrier. When transporting large-sized cut pieces, a disc carrier should be used. When transporting semi-finished garments, a hanger-type vehicle should be used. Match the appropriate model of intelligent transportation equipment according to the type of transport vehicle and load requirements.

4. The multi-vehicle pattern piece transportation scheduling method based on a work hour system according to claim 1, characterized in that, The target intelligent delivery equipment for performing the logistics transfer task includes: Obtain the online status, current location, power status, load status, and current task status of each intelligent delivery device in the intelligent delivery device cluster; Based on the priority of the logistics transfer task, the current location of the equipment, and the operating status of the equipment, the target intelligent transport equipment is determined from the intelligent transport equipment cluster.

5. The multi-vehicle pattern piece transportation scheduling method based on a work hour system according to claim 1, characterized in that, The intelligent transport device for controlling the target executes the cut piece transport task according to the device control instructions, including: Receive equipment control commands sent by the intelligent scheduling system; According to the equipment control instructions, the intelligent conveying equipment is controlled to move to the material picking position and complete the loading of the cut material; Control the intelligent conveying equipment to move to the target location and complete the unloading of the cut materials; During transportation, the status of obstacles in the transportation area is detected by a visual perception module.

6. The multi-vehicle pattern piece transportation scheduling method based on a work hour system according to claim 1, characterized in that, The adjustment of the travel route according to changes in the transportation environment includes: The SLAM navigation module acquires environmental information about the operating area of ​​the intelligent transportation equipment and constructs a spatial map that includes production equipment, transportation channels, and work areas. A three-dimensional potential energy field model is established based on the spatial map, with the target location of the logistics transfer task as the target constraint area and the areas where production equipment, personnel areas and other intelligent transportation equipment are located as obstacle constraint areas. The direction of movement of the intelligent transport equipment is determined based on the three-dimensional potential energy field model, and the movement path is adjusted in combination with the dynamic environmental information collected by the visual perception module.

7. The multi-vehicle pattern piece transportation scheduling method based on a work hour system according to claim 1, characterized in that, The step of feeding back the status information to the work hour management system includes: The intelligent scheduling system aggregates the location status, operating status, and task execution status uploaded by the intelligent transportation equipment. Establish a logistics task status record based on the task identification information; The logistics task status record is sent to the time management system, which then updates the logistics time data based on the fabric delivery time, task completion time, and process waiting time.

8. The multi-vehicle cut piece transportation scheduling method based on a work hour system according to claim 1, characterized in that, The step of restoring the logistics transfer task based on the breakpoint snapshot includes: When the intelligent delivery equipment experiences communication abnormalities, equipment failures, or stops running, it saves the current task identification information, equipment location, and completed task steps to form a breakpoint snapshot. After the anomaly is recovered, the current position of the intelligent delivery equipment is verified based on the breakpoint snapshot; The time management system confirms that the corresponding logistics transfer task is still in active execution and that there is still a material requirement at the target production location. Based on the verification results, a task resumption execution instruction is generated, enabling the intelligent transportation equipment to continue performing the remaining transportation tasks.

9. The multi-vehicle pattern piece transportation scheduling method based on a work hour system according to claim 1, characterized in that, The multi-vehicle cut piece transportation and scheduling method also includes: Connect the time management system to the external production management system via a communication interface; The external production management system includes an Enterprise Resource Planning (ERP) system, a Manufacturing Execution System (MES) system, and a Warehouse Management System (WMS). By acquiring production order information, inventory information, and logistics task information through data interaction, collaborative logistics management can be achieved during the production and manufacturing process.

10. A multi-vehicle pattern piece transportation scheduling system based on a work-hour system, to implement the multi-vehicle pattern piece transportation scheduling method based on a work-hour system according to any one of claims 1-9, characterized in that, The multi-vehicle pattern delivery and scheduling system includes: a core command module for a time management system, a core module for intelligent scheduling, and an execution module for intelligent delivery equipment. The core command module of the time management system is used to acquire production order information, time information, inventory information, and production line material demand information. It generates logistics transfer tasks based on the needs of fabricated piece transportation and manages the addition, editing, pausing, termination, and priority adjustment of these tasks. Simultaneously, the core command module connects with the production line system and the warehousing business system to associate production work order information and inventory information, and receives real-time feedback from intelligent transportation equipment on equipment status, task execution status, and logistics completion information. The intelligent scheduling core module communicates with the core command module of the work hour management system. It is used to receive logistics transfer tasks, parse and break down the logistics transfer tasks, and generate execution instructions adapted to a single intelligent transport device, multiple intelligent transport devices, or intelligent transport devices of different vehicle frame types according to the type of cut pieces, transportation needs, and execution requirements. At the same time, it obtains the online status, current location, power status, load status, and task execution status of the intelligent transport devices, determines the target intelligent transport device according to the priority of the logistics transfer task, the operating status of the equipment, and the transportation distance, and generates corresponding scheduling instructions. The intelligent scheduling core module is also used to plan routes based on the factory environment information and the operating status of intelligent transportation equipment. It adjusts the transportation route by combining preset transportation routes with real-time environmental perception data, and analyzes and processes route conflicts, point occupancy and operation deadlocks that occur when multiple intelligent transportation equipment are running at the same time, so as to realize the collaborative operation of multiple equipment. The intelligent conveying equipment execution module is communicatively connected to the intelligent scheduling core module and is used to receive scheduling instructions and execute the cut piece transportation task. The intelligent conveying equipment execution module includes an autonomous navigation unit, a visual obstacle avoidance unit, a precise docking unit, an automatic material picking and placing unit, a status detection unit, an emergency braking unit, and a task recovery unit. The task recovery unit is used to save the status of the currently executing task when the intelligent transportation equipment experiences a power outage, emergency stop, communication disconnection, malfunction shutdown, or manual pause, resulting in task interruption. This creates a task snapshot containing task information, equipment location information, transportation path information, and material information. Based on task segmentation marking information and a recovery verification mechanism, the task snapshot is read after the equipment resumes operation, and the remaining transportation tasks are continued from the point of task interruption. The core command module of the work hour management system also includes a data visualization unit and an anomaly management unit. The data visualization unit is used to build a logistics operation status display interface to visualize the location status of intelligent transportation equipment, task completion rate, and logistics operation efficiency. The anomaly management unit is used to detect, warn, push information, and record the handling of anomalies during transportation, so as to realize closed-loop management of logistics task anomaly handling. Through data interaction between the core command module, intelligent scheduling core module, and intelligent transportation equipment execution module of the time management system, the entire process of fabrication logistics task generation, intelligent equipment scheduling, transportation execution, status feedback, and anomaly recovery is achieved through collaborative control.

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