TW202311882A - Material handling method based on digital twin - Google Patents

Abstract

A processing method comprises: (a) inputting a product order table to a fleet management system; (b) generating a navigation plan table according to the product order table and controlling the mobile robot to process the material according to the navigation plan table by the fleet management system; (c) building a digital twin model based on real-time physical parameters by a digital twin building unit; (d) simulating a result of the mobile robot executing the navigation plan table by the digital twin model; (e) providing a simulation result from the digital twin model to the fleet management system; (f) evaluating whether the simulation result meet an expected condition; wherein when the simulation result in step (f) does not meet the expected condition, the fleet management system adjusts the navigation plan table, and controls the mobile robot to process the materials according to the adjusted navigation plan table.

Description

Material handling method based on digital twin

This case belongs to the field of material handling, especially a material handling method and material handling system.

At present, the industry has been trying to form a material handling system by integrating automation facilities such as conveyor systems, gantry robots, and carousels to improve the efficiency of factory logistics. These automation facilities are designed to reduce The labor cost and lead time of the materials used in the production process. Such facilities can also be found in many of today's Surface Mount Technology (SMT) manufacturing processes, whereby different types of components to be placed on printed circuit boards are delivered to the assembly line. In the manufacturing process of surface bonding technology, automatic guided vehicles (AGV) have also been developed for the handling and arrangement of factory goods. Because the current automatic guided vehicles are automated, high-efficiency, and less prone to errors, etc. Advantages, it has been widely used in factory logistics using material handling systems.

However, traditional material handling systems usually passively update and modify the operation mode of the corresponding automation facilities according to changes in the environment (such as the type of project delivered and/or the layout of the manufacturing workshop, etc.), resulting in increased costs, and even worse, Traditional material handling systems also have the problem of high maintenance costs. In summary, traditional material handling systems are difficult to adapt to the ever-changing market.

Much of manufacturing is now closely tied to the software technologies and algorithms that create so-called cyber-physical systems (CPS). The gap between physical (factory) and network (software) interconnections has narrowed significantly with the recent emergence of the concept of a digital twin, which enables real-time, bi-directional representations of reality in digital space operation to achieve the purpose of optimizing operational efficiency.

Therefore, this case is proposed based on the concept of applying digital twin technology to materials for surface bonding technology, in order to improve the lack of the aforementioned traditional material handling system, and to achieve the effect that the aforementioned traditional material handling cannot achieve.

The purpose of this case is to provide a material processing method and material processing system, which can achieve real-time and online processing of materials applied to surface bonding technology, and can dynamically change route planning in response to changes in product order forms, and can respond to mobile shelves. And plan the route, and provide prediction and optimization according to the real-time data of the factory.

The purpose of this case is to provide a material processing method and material processing system, which do not require expensive installation costs, maintenance costs, update and modification costs, and do not require long installation time and complicated software systems.

In order to achieve the above-mentioned purpose, a preferred implementation aspect of this case provides a material processing method, which is applied to the material processing system in the factory, wherein the material processing system processes the materials used in surface bonding technology, and includes movable The robot, the fleet management system controlling the mobile robot and the digital twin construction unit, the material processing method includes: executing the material processing program, including: (a) inputting the product order form to the fleet management system; (b) the fleet management system according to the product order form Generate a navigation plan, and control the mobile robot to move and operate according to the movement path and operation mode planned by the navigation plan to process materials; (c) the digital twin construction unit receives real-time sensed information about the factory Real-time physical parameters for initialization operation, and then establish a digital twin model based on the real-time physical parameters; (d) use the digital twin model to simulate the results of the mobile robot executing the navigation plan to generate the first simulation result; (e) The first simulation result is provided to the fleet management system; (f) the fleet management system evaluates whether the first simulation result meets the expected condition; and (g) when the fleet management system evaluates the simulation result in step (f) meets the expected condition, then re Execute step (c), when the fleet management system in step (f) evaluates that the simulation result does not meet the expected conditions, the fleet management system adjusts the navigation plan, and controls the mobile robot to move according to the adjusted navigation plan Move and operate according to the path and operation mode to process the material.

In order to achieve the aforementioned purpose, another preferred embodiment of this case provides a material handling system, which is used in factories to process materials used in surface bonding technology, and includes: at least one mobile robot; The management system is used to generate the navigation plan table according to the product order form, and control the mobile robot to move and operate according to the movement path and operation mode planned by the navigation plan table, so as to process the materials; and the digital twin construction unit , to receive the real-time physical parameters of the factory sensed in real time, and establish a digital twin model based on the real-time physical parameters; where in the process of the mobile robot processing materials, the digital twin construction unit uses the digital twin model to simulate the mobile The robot executes the results of the navigation plan to generate the first simulation result correspondingly, and the fleet management system evaluates whether the first simulation result meets the expected conditions, and adjusts the navigation plan when the first simulation result does not meet the expected conditions, and Control the mobile robot to move and operate according to the movement path and operation mode planned by the adjusted navigation plan, so as to process the materials.

Some typical embodiments embodying the features and advantages of the present application will be described in detail in the description in the following paragraphs. It should be understood that this case can have various changes in different aspects, all of which do not depart from the scope of this case, and the descriptions and diagrams therein are used for illustration in nature, rather than to limit this case.

Please refer to Figure 1 and Figure 2, wherein Figure 1 is a schematic diagram of the system architecture of the material handling system in a preferred embodiment of this case, and Figure 2 is a schematic diagram of the control structure of the material handling system shown in Figure 1. As shown in Figure 1 and Figure 2, the material handling system 100 of this case can be but not limited to be applied in a factory, where materials such as but not limited to surface bonding technology are placed in the factory, and the materials include various sizes and component reels (reels) of different weights applied to the surface bonding technology, and the material handling system 100 can input a product order form, and transfer and process the materials in the factory according to the product order form. The material handling system 100 includes a buffer area 101 with multiple configurations, at least one mobile robot, a mobile rack 106, a production unit 107, a plurality of production lines 108, a fleet management system (Fleet Management System) 110 and a digital twin Construction unit 111. The product order form can record, but is not limited to, the sequence of various materials, the selected production line 108, the cut-off time for the materials to arrive at the selected production line 108, and the form and weight of the materials sent to the selected production line 108, etc. In addition, there may be multiple mobile robots. For example, the multiple mobile robots shown in FIG. , 103 and automatic guided vehicles 104, 105 of the same or different sizes.

The production unit 107 is used to provide materials. The plurality of production lines 108 can respectively process and process the received materials to complete the final physical product. The mobile rack 106 can be transferred between different areas of the factory floor, and the mobile rack 106 can hold materials, that is, component reels, which will be transferred to the designated production line 108 according to the content of the requested product order form. The buffer zone 101 is located between the production unit 107 and the production line 108 , and the buffer zone 101 can accommodate at least one mobile rack 106 .

The autonomous mobile robots 102, 103 and the automatic guided vehicles 104, 105 are wirelessly controlled by the fleet management system 110 to automatically move and operate, wherein the automatic guided vehicles 104, 105 can be attached to the mobile rack 106 or from In addition, the automatic guided vehicles 104 and 105 transport the mobile racks 106 in the buffer zone 101 to the vicinity of specific autonomous mobile robots 102 and 103 based on the arrangement of the fleet management system 110, respectively, or The mobile racks 106 in the vicinity of the autonomous mobile robots 102 , 103 or at other locations in the factory are transported to the buffer zone 101 . In some embodiments, the number of automated guided vehicles may be less than the number of mobile racks 106 . The fleet management system 110 can input a product order form, and generate a navigation plan table according to the record content in the product order form, wherein the navigation plan table plans the autonomous mobile robots 102, 103 and automatic guided vehicles 104 and 105. path, whereby the autonomous mobile robots 102, 103 and the automatic guided vehicles 104 and 105 can perform corresponding autonomous movements according to the navigation plan.

In some embodiments, depending on the order in which the materials are arranged in the production order table, the mobile racks 106 in the buffer zone 101 can be based on a First-In-First-Out (FIFO) basis or a task-oriented basis Arranging in sequence, wherein the first-in-first-out basis depends on the fleet management system 110 arranging the mobile racks 106 according to the order of materials recorded in the production order table. The basis of task orientation is to arrange the mobile racks 106 based on the specific priorities planned in the tasks received by the fleet management system 110 .

The autonomous mobile robots 102, 103 respectively move materials into/out of the mobile racks 106 in the buffer zone 101 based on the control of the fleet management system 110. On the mobile rack 106 , the autonomous mobile robot 103 can remove the materials on the mobile rack 106 in the buffer zone 101 and transfer them to any production line 108 . Furthermore, each autonomous mobile robot 102, 103 actually consists of a robot manipulator to which a mobile drive unit (not shown) is attached. Furthermore, the autonomous mobile robot 102, 103 can sort the component reels according to the type of the component reels and the sequential arrangement of the production order table with respect to the component reels. When the autonomous mobile robots 102, 103 complete the transfer of the component reels, the mobile racks 106 adjacent to the autonomous mobile robots 102, 103 can be moved back to the buffer zone 101 by the automatic guided vehicles 104, 105.

In some embodiments, as shown in FIG. 2 , the material handling system 100 may include a centralized communication middleware 109 . In addition, the material handling system 100 in this case can be roughly divided into three parts according to the control structure. The lowest-level part is the controlled body, which includes autonomous mobile robots 102, 103 and automatic guided vehicles 104 and 105. The middle-level part is Signal management and transmission are realized by the centralized communication intermediary software 109 , and the highest-level part is the control body, which includes the fleet management system 110 and the digital twin construction unit 111 . The centralized communication intermediary software 109 transmits and converts the data packets and/or control signals output by the fleet management system 110 to the autonomous mobile robots 102, 103 and the automatic guided vehicles 104 and 105, so that the fleet management system 110 can control the autonomous mobile robot 102 , 103 and automatic guided vehicles 104 and 105 to perform corresponding operations. In addition, the centralized communication intermediary software 109 will further connect the autonomous mobile robots 102 and 103 and the automatic guided vehicles 104 and 105 through their own or external sensors (not shown As shown in the figure), the sensed operating parameters are converted and transmitted to the fleet management system 110 and/or the digital twin construction unit 111, so that the centralized communication intermediary software 109 actually manages the output from the fleet management system 110 and the digital twin construction unit 111 respectively And the key information received respectively. The digital twin construction unit 111 is based on real-time physical parameters sensed by various sensors (not shown) in the factory (real-time physical parameters include the environment in the factory and structural parameters and/or operating parameters of various facilities, etc.) The digital twin model is established, and there is a virtual-real mapping relationship between the real-time physical parameters in the factory and the digital twin model established by the digital twin construction unit 111. In addition, the digital twin construction unit 111 processes, predicts and optimizes based on real-time physical data, and according to The preset control of the fleet management system 110 immediately adopts the optimal task arrangement, and notifies the fleet management system 110 of the arrangement result, so that the fleet management system 110 can perform corresponding control and adjustment. In the above-mentioned embodiments, the digital twin model can be, but not limited to, include the digital twin models of the automatic guided vehicles 104, 105, the digital twins of the autonomous mobile robots 102, 103, and the digital twin models of other facilities in the factory.

Please refer to Figure 3, and cooperate with Figure 1 and Figure 2, wherein Figure 3 is a flow chart of the steps of the material handling method applied in the material handling system shown in Figure 1 when executing the material handling procedure. As shown in Figures 1 to 3, the material handling method in this case will implement a material handling procedure, which includes the following steps.

Step S200: Input the product order form to the fleet management system 110.

Step S201: The fleet management system 110 generates a navigation plan table according to the product order table, and controls the mobile robot (including the autonomous mobile robots 102, 103 and the automatic guided vehicles 104 and 105) to plan the movement path and The operation mode is to move and operate to process the material.

Step 202: The digital twin construction unit 111 receives the real-time physical parameters of the factory sensed immediately to perform initialization operation, and then builds a digital twin model according to the real-time physical parameters.

Step S203: using the digital twin model to simulate the result of the mobile robot executing the navigation plan, so as to generate a first simulation result correspondingly.

Step S204: Provide the first simulation result to the fleet management system 110.

Step S205: The fleet management system 110 evaluates whether the first simulation result meets an expected condition (the expected condition is preset, and the expected condition can be, for example, that the simulation result meets the cut-off time for the materials recorded in the product order form to arrive at the selected production line 108 wait).

When the fleet management system 110 evaluates that the simulation result meets the expected condition in step S205, step S202 is re-executed. In some embodiments, after step S205 is executed, step S202 is re-executed after a set time has elapsed.

Step S206: When the fleet management system 110 evaluates that the simulation result does not meet the expected conditions in step S205, the fleet management system 110 adjusts the navigation plan, and controls the mobile robot to move according to the adjusted navigation plan. The operation mode is to move and operate to process the material. After step S206 is executed, step S202 is re-executed. In some embodiments, after step S206 is executed, step S202 is re-executed after a set time has elapsed.

It can be seen from the above that the material processing method and the material processing system 100 in this case can be simulated simultaneously by using the digital twin model established by the digital twin construction unit 111 based on real-time physical parameters during the process of the mobile robot moving and operating to process the material The results of the mobile robot's execution of the navigation plan are used to predict whether the movement and operation results of the mobile robot can meet the content recorded in the product order form, and when the simulation results do not meet the expected conditions, the navigation plan can be adjusted at any time. The movement and operation of the mobile robot are optimized, so the material handling method and material handling system in this case can respond to various environmental or parameter changes, such as changes in the product order list and changes in the position of the mobile shelf, etc., and dynamically adjust the navigation plan The route planning in the table is adjusted so that the material handling system 100 can complete the content recorded in the product order table. In addition, through the digital twin model established by the digital twin construction unit 111 based on real-time physical parameters to simulate various behaviors or parameters in the factory, the material handling system 100 in this case can actively adjust the operation of each facility according to changes in the environment , so the maintenance cost, update and modification cost of the material handling system 100 can be reduced, and long installation time and complicated software systems are not required.

Please refer to Figure 4, and cooperate with Figures 1 to 4, wherein Figure 4 is a flow chart of the steps of the material handling method in this case when performing the charge prediction program. As shown in FIG. 1 to FIG. 4 , in some embodiments, the material processing method of the present application further implements a charge prediction procedure, and the charge prediction procedure includes the following steps.

Step S300: When the real-time physical parameters reflect that the current power of any mobile robot is equal to or less than a first preset power threshold and is in a low power state, use the digital twin model to simulate the mobile robot in the low power state according to the real-time physical parameters The mobile robot moves to the end point of the movement path planned by the navigation plan table.

Step S301: using the digital twin model to simulate the movement of the mobile robot in a low battery state from the end of the movement path towards the charging station, and generating a second simulation result.

Step S302: Provide the second simulation result to the fleet management system 110, so that the fleet management system 110 evaluates whether the mobile robot in the low battery state can move from the end of the moving path to the charging station according to the remaining power according to the second simulation result.

Step S303: When the fleet management system 110 evaluates in step S302 that the mobile robot in the low battery state can move from the end of the movement path to the charging station according to the remaining power, the fleet management system 110 controls the mobile robot to move according to the navigation plan . After step S303 is executed, step S300 is re-executed.

Step S304: When the fleet management system 110 evaluates in step S302 that the mobile robot in the low battery state cannot move from the end of the moving path to the charging station according to the remaining power, the fleet management system 110 controls the mobile robot in the low battery state to return to charging The station is fully charged to the second preset power threshold. After step S304 is executed, step S303 is re-executed. In this embodiment, the second preset power threshold is greater than the first preset power threshold.

In some embodiments, when the material processing method executes the material processing program so that the mobile robot processes the material and the digital twin model has been established, the material processing method can simultaneously execute the charging prediction program, but not limited thereto, In other embodiments, the charge prediction procedure is executed prior to the material handling procedure.

With the charge prediction program executed by the aforementioned material handling method, the material handling system 100 of this case does not need to control the mobile robot when the current battery power is equal to or lower than the first preset power threshold and is in a low power state. The mobile robot is charged, but the mobile robot is controlled to charge when it is judged that the mobile robot cannot successfully complete the navigation plan and returns to the charging station for charging, so the charging times of the mobile robot can be reduced and the use efficiency can be improved.

Please refer to Figure 5, and cooperate with Figures 1 to 3, wherein Figure 5 shows a schematic diagram when the digital twin model established by the digital twin building unit shown in Figure 1 is composed of multiple sub-models. As shown in FIG. 5, in some embodiments, the digital twin model 400 established by the digital twin construction unit 111 can be composed of at least one sub-model, and as shown in FIG. 5, the digital twin model 400 established by the digital twin construction unit 111 The model 400 is composed of a plurality of interconnected sub-models, and the plurality of sub-models are composed and simulated in a Globally Asynchronous and Formally Synchronous (GALS) manner. The digital twin 400 consists of one or more top-level asynchronous behaviors (aka processes) called clock-domains, such as clock-domain 401 , clock-domains 407 and 408 . In each clock domain, there are one or more synchronization behaviors (also known as threads), such as synchronization behaviors 402, 403, 406 in the clock domain 401, synchronization behavior 407a in the clock domain 407, and synchronization behaviors in the clock domain 407. Synchronous behaviors 404, 405 in the pulse domain 408, these synchronization behaviors in the clock domain are respectively executed in a locked-step manner according to the logical scale of the corresponding clock domain, while the autonomous mobile robots 102, 103 and the automatic guided vehicle The sub-models corresponding to 104 and 105 respectively, as well as the internal state of the mobile rack 106 and the operation of the material handling system 100 are described in this form. In addition, closely related behaviors are grouped into the same clock domain, while the synchronous part is defined in terms of global asynchronous local synchronization, i.e. all behaviors in the same clock domain are simulated in a deterministic manner, e.g. autonomous The submodels of the mobile robot 102 and the production cell 107 mostly work together in close quarters, and in this case the simulations of the autonomous mobile robot 102 and the production cell 107 are synchronized so that any communication between the two models is Decide whether its simulation will take place locally or in a distributed computing environment. The digital twin model 400 established by the digital twin construction unit 111 is composed of a plurality of interconnected sub-models, and the plurality of sub-models are composed and simulated in a global asynchronous and local synchronous manner, so this case can achieve the following advantages, namely Improving the ability of mobile robots to predict deadlines and battery consumption of mobile robots based on navigation planning by deterministic simulations in the single-clock domain ability, due to the asynchronous relationship of different clock domains, models simulated in two different clock domains communicate through a first-in-first-out sequence (such as the sequence 409, 410, 411, 412 shown in Figure 5), and this Combination achieves scalability by eliminating synchronization constraints between clock domains, so digital twins that allow combination in a globally asynchronous locally synchronized manner can be applied to larger-scale material handling systems for surface-attachment technology.

To sum up, this case provides a material processing method and a material processing system, which can use the digital twin model to simulate the mobile robot in real time during the process of the mobile robot moving and operating to process the material Execute the results of the navigation plan, and then predict and optimize the movement and operation of the mobile robot at any time, so as to achieve the effect of improving the overall efficiency and cost of the material handling system.

100:Material Handling System 101: buffer 102, 103: Autonomous mobile robots 104, 105: Automatic guided vehicles 106: Mobile shelf 107: Production unit 108: Production line 109:Centralized communication intermediary software 110: Fleet management system 111:Digital twin building blocks 400: Digital Twins 401, 407, 408: clock domain 402, 403, 404, 405, 406, 407a: synchronous behavior 409, 410, 411, 412: sequence S200~S206: the steps of executing the material handling procedure in the material handling method S300~S304: the steps of executing the charge prediction program in the material handling method

Figure 1 is a schematic diagram of the system architecture of the material handling system of the preferred embodiment of this case; Figure 2 is a schematic diagram of the control structure of the material handling system shown in Figure 1; Figure 3 is a flow chart of the steps of the material handling method applied to the material handling system shown in Figure 1 when executing the material handling procedure; Figure 4 is a flow chart of the steps of the material handling method in this case when executing the charge prediction program; FIG. 5 is a schematic diagram showing a digital twin model established by the digital twin building unit shown in FIG. 1 consisting of multiple sub-models.

S200~S206: the steps of executing the material handling procedure in the material handling method

Claims (11)

A material processing method applied in a material processing system in a factory, wherein the material processing system processes a material used in surface bonding technology, and includes a mobile robot, a fleet of mobile robots that control the mobile robot Management system and a digital twin building block, the material handling method includes: Execute a material handling program, including: (a) Input a product order form into the fleet management system; (b) The fleet management system generates a navigation plan based on the product order form, and controls the mobile robot to move and operate according to the movement path and operation mode planned by the navigation plan, so as to process the material ; (c) The digital twin construction unit receives a real-time physical parameter of the factory sensed in real time to perform initialization operations, and then builds a digital twin model based on the real-time physical parameter; (d) using the digital twin model to simulate the result of the mobile robot executing the navigation plan to generate a corresponding first simulation result; (e) providing the first simulation results to the fleet management system; (f) the fleet management system assesses whether the first simulation result meets a desired condition; and (g) When the fleet management system in step (f) evaluates that the simulation result meets the expected condition, re-execute the step (c), when the fleet management system in step (f) evaluates that the simulation result does not meet the expected condition When the conditions are expected, the fleet management system adjusts the navigation plan, and controls the mobile robot to move and operate according to the movement path and operation mode planned by the adjusted navigation plan, so as to process the material, And re-execute the step (c). The material processing method as described in claim 1, wherein the material processing method further executes a charge prediction program, including: (h) when the real-time physical parameter reflects that the current power of any one of the mobile robots is equal to or less than a first preset power threshold and is in a low power state, using the digital twin model to simulate being in the state according to the real-time physical parameter The mobile robot in the low battery state moves to an end point of a movement path planned by the navigation plan; (i) using the digital twin model to simulate the movement of the mobile robot in the low battery state from the end point of the movement path towards a charging station, and generating a second simulation result; (j) providing the second simulation result to the fleet management system, so that the fleet management system evaluates whether the mobile robot in the low battery state can move from the end point of the movement path according to the remaining power according to the second simulation result to the charging station; (k) When the fleet management system evaluates that the mobile robot in the low battery state can move from the end point of the movement path to the charging station according to the remaining power in the step (j), the fleet management system controls the low battery The mobile robot in the power state moves according to the navigation plan, and re-executes the step (h); and (l) When the fleet management system in the step (j) evaluates that the mobile robot in the low battery state cannot move from the end point of the movement path to the charging station according to the remaining power, the fleet management system controls the low battery The mobile robot in the state returns to the charging station to be fully charged to a second preset power threshold, and re-executes the step (h). The material processing method as described in Claim 2, wherein when the material processing method executes the material processing program so that the mobile robot processes the material and the digital twin model has been established, the material processing method is executed synchronously The charge prediction program. The material handling method as described in claim 1, wherein the material handling system further comprises at least one mobile shelf for accommodating the material, and in the step (b), the fleet management system controls the mobile robot to attach to or from the mobile rack to process the material. The material handling method as described in claim 1, wherein the material handling system further includes a buffer zone, the buffer zone is used to place the mobile shelf, and the mobile shelf in the buffer zone is based on a first-in-first-out basis or Task-oriented basis for sequential arrangement. The material processing method as described in Claim 1, wherein the digital twin model is composed of multiple sub-models connected to each other, and the multiple sub-models are respectively composed and simulated by a global asynchronous local synchronization method. A material handling system, applied in a factory, is used to process a material used in surface bonding technology, and includes: at least one mobile robot; A fleet management system, used to generate a navigation plan based on a product order form, and control the mobile robot to move and operate according to the movement path and operation mode planned by the navigation plan, so as to process the material ;as well as A digital twin construction unit is used to receive the real-time physical parameters of the factory sensed in real time, and build a digital twin model according to the real-time physical parameters; Wherein, during the process of the mobile robot processing the material, the digital twin construction unit uses the digital twin model to simulate the result of the mobile robot executing the navigation plan to generate a corresponding first simulation result, and the The fleet management system evaluates whether the first simulation result meets an expected condition, and when the first simulation result does not meet the expected condition, adjusts the navigation plan and controls the mobile robot according to the adjusted navigation plan Move and operate according to the movement path and operation mode planned in the table to process the material. The material handling system as described in claim 7, wherein when the real-time physical parameter reflects that the current power of any one of the mobile robots is equal to or less than a first preset power threshold and is in a low power state, the digital twin is constructed The unit uses the digital twin model to first simulate the mobile robot in the low battery state moving to an end point of a movement path planned by the navigation plan according to the real-time physical parameters, and then simulates the mobile robot in the low battery state. The mobile robot moves towards a charging station from the end point of the moving path, and generates a second simulation result, and the fleet management system evaluates whether the mobile robot in the low battery state can be charged from the charging station according to the remaining power according to the second simulation result. The end point of the moving path moves to the charging station, and when the evaluation result is that the mobile robot in the low battery state can move from the end point of the moving path to the charging station according to the remaining power, controlling the mobile robot in the low battery state The mobile robot moves according to the navigation plan, and when the evaluation result is that the mobile robot in the low battery state cannot move from the end point of the movement path to the charging station according to the remaining battery power, control the charging station in the low battery state The mobile robot returns to the charging station to be fully charged to a second preset power threshold. The material handling system as described in claim 7, further comprising at least one mobile rack for containing the material, and the fleet management system controls the mobile robot to be attached to or removed from the mobile rack Disassemble for disposal of the material. The material handling system as described in claim 9, further comprising a buffer zone, the buffer zone is used to place the mobile rack, and the mobile rack in the buffer zone is performed on a first-in first-out basis or a task-oriented basis in order. The material handling system as described in Claim 7, wherein the digital twin model is composed of a plurality of interconnected sub-models, and the plurality of sub-models are respectively composed and simulated in a global asynchronous and local synchronous manner.

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