Semiconductor production material carrying scheduling method, device and equipment and readable storage medium

Abstract

The invention discloses a semiconductor production material carrying scheduling method, device and equipment and a readable storage medium, and relates to the field of production scheduling. According to the method, all the sub-tasks of the material carrying task are used as the minimum task sorting units to be sorted, all possible task execution sequences are obtained, and the optimal execution sequence is screened out from all the possible task execution sequences with the purpose of finding the shortest path. According to the method, the material carrying task is more flexible to execute, the proportion of the no-load stroke of the AGV can be reduced, and the transportation efficiency of the AGV is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of production scheduling, and in particular to a semiconductor production material handling scheduling method, device, equipment and readable storage medium. BACKGROUND

[0002] In the field of semiconductor manufacturing, the manufacturing process flow of wafers is long, and the complex process flow can reach five or six hundred steps. These processes involve a large number of devices and types. In the early stage, the handling of wafers was basically completed by manpower. With the continuous development of wafer production technology, the size of the wafer gradually increases, and manual handling is difficult to meet the wafer handling needs. At the same time, considering the safety problems in the handling process, the yield of wafers and the actual production needs, introducing automated handling equipment has become an inevitable trend.

[0003] The material control system (MCS) is a system for managing automated handling equipment, which has been applied in wafer factories. In the wafer factory, the MCS mainly manages the automated guided vehicle (AGV), the rail guided vehicle (RGV) and the overhead hoist vehicle (OHT).

[0004] The OHT and the RGV travel on a pre-set track. Once the track is laid, subsequent track modification will be relatively complex and expensive. The AGV has less dependence on the track than the OHT and the RGV, and the difficulty of modification is reduced. Based on the advantage of the AGV, it is necessary to manage the transportation process of the AGV.

[0005] The management of the transportation process of the AGV includes the management of the number of AGVs, the scheduling management of the AGVs, and the management of the travel route of the AGVs. In the production process of semiconductor products, the tasks to be performed by the AGV can be divided into two categories: "pick up" type tasks (the AGV needs to go to the current location of the task, and the mechanical arm on the AGV picks up the task and then puts it on the AGV), and "put down" type tasks (after the "pick up" task is completed, the AGV can be sent to the destination of the task). In the case of multiple tasks, how to reasonably arrange the order of the AGV to perform the task is one of the important problems to be solved in the scheduling management of the AGV.

[0006] The purpose of the AGV scheduling method is to arrange the AGV to perform the material handling task in the order of the task. However, in this method, the empty travel distance of the AGV accounts for a high proportion in the production process of the AGV, and the corresponding AGV handling efficiency is low, which affects the overall efficiency of the wafer production.

[0007] The above merely serves to assist in understanding the technical solutions of the present application and does not represent an acknowledgement that the above is prior art. SUMMARY

[0008] The main purpose of the present application is to provide a semiconductor production material handling scheduling method, device, equipment and readable storage medium, aiming at solving the technical problem that the current AGV handling efficiency is low, which affects the overall efficiency of wafer production.

[0009] To achieve the above purpose, the present application provides a semiconductor production material handling scheduling method, which comprises the following steps:

[0010] Generating a set of optional task execution sequences based on each current to-be-executed task of the AGV, wherein the current to-be-executed task is a subtask of the material handling task of the AGV;

[0011] Obtaining one task execution sequence from the set of optional task execution sequences as a current task execution sequence;

[0012] Generating a current shortest path when the AGV completes each current to-be-executed task based on the current task execution sequence according to a preset execution scene model of the AGV, and comparing the current shortest path with an existing shortest path;

[0013] If the current shortest path is less than the existing shortest path, then taking the current shortest path as a new existing shortest path and taking the current task execution sequence as a new optimal execution sequence;

[0014] Deleting the current task execution sequence from the set of optional task execution sequences to generate a new set of optional task execution sequences, executing the step of obtaining one task execution sequence from the set of optional task execution sequences as a current task execution sequence until the set of optional task execution sequences is empty, outputting the optimal execution sequence, and scheduling the AGV based on the optimal execution sequence.

[0015] Further, after the step of comparing the current shortest path with the existing shortest path, the method comprises:

[0016] If the current shortest path is greater than or equal to the existing shortest path, then keeping the existing shortest path and the optimal execution sequence unchanged;

[0017] Executing the step of deleting the current task execution sequence from the set of optional task execution sequences to generate a new set of optional task execution sequences.

[0018] Further, after the step of obtaining a task execution sequence from the set of optional task execution sequences as a current task execution sequence, the method comprises:

[0019] determining whether the AGV will be overloaded when executing each of the current to-be-executed tasks based on the current task execution sequence;

[0020] if not, performing the step of generating the current shortest path of the AGV when executing each of the current to-be-executed tasks based on the current task execution sequence according to the preset execution scene model of the AGV;

[0021] if yes, performing the step of deleting the current task execution sequence from the set of optional task execution sequences to generate a new set of optional task execution sequences.

[0022] Further, the current to-be-executed task is a picking task or a placing task, and the step of determining whether the AGV will be overloaded when executing each of the current to-be-executed tasks based on the current task execution sequence comprises:

[0023] obtaining, in sequence, execution positions at which the AGV stays when executing each of the current to-be-executed tasks based on the current task execution sequence;

[0024] obtaining a first number of picking tasks to be executed and a second number of placing tasks to be executed at the execution positions;

[0025] obtaining a number of objects to be loaded on the AGV at the execution positions by subtracting the second number from a sum of the first number and a third number of objects already loaded on the AGV;

[0026] comparing the number of objects with a preset maximum capacity of the AGV;

[0027] if there is an execution position corresponding to the number of objects greater than the preset maximum capacity, it is determined that the AGV will be overloaded;

[0028] if there is no execution position corresponding to the number of objects greater than the preset maximum capacity, it is determined that the AGV will not be overloaded.

[0029] Further, the step of generating the current shortest path of the AGV when executing each of the current to-be-executed tasks based on the current task execution sequence according to the preset execution scene model of the AGV comprises:

[0030] determining a current position of the AGV in the preset execution scene model;

[0031] calling a preset shortest path planning algorithm to generate a shortest preparation path of the AGV in the preset execution scene model from the current position to a starting point of a current to-be-executed task, wherein the starting point of the current to-be-executed task is a first current to-be-executed task in the current task execution sequence;

[0032] calling the preset shortest path planning algorithm to generate a shortest execution path of the AGV in the preset execution scene model when completing each current to-be-executed task according to the current task execution sequence;

[0033] adding the shortest preparation path and the shortest execution path to obtain the current shortest path.

[0034] Further, the step of calling the preset shortest path planning algorithm to generate the shortest execution path of the AGV in the preset execution scene model when completing each current to-be-executed task according to the current task execution sequence comprises:

[0035] obtaining each execution position of the AGV in the preset execution scene model according to the current task execution sequence, wherein the arrangement order of each execution position corresponds to the current task execution sequence;

[0036] obtaining a node shortest path between each adjacent execution position from the preset execution scene model;

[0037] sequentially connecting and combining each node shortest path to obtain the shortest execution path.

[0038] Further, the method for generating a selectable task execution sequence set based on each current to-be-executed task of the AGV comprises:

[0039] when receiving a new material handling task, decomposing the material handling task to obtain a subtask, wherein the subtask is a taking task or a placing task;

[0040] taking the taking task as the current to-be-executed task of the AGV;

[0041] when the taking task is executed and completed, taking the placing task corresponding to the taking task as the current to-be-executed task.

[0042] In addition, to achieve the above object, the application further provides a semiconductor production material handling scheduling device, which comprises:

[0043] The first generating module is configured to generate a set of optional task execution sequences based on the current to-be-executed tasks of the AGV, wherein the current to-be-executed tasks are subtasks of the material handling tasks of the AGV.

[0044] The acquisition module is configured to acquire one task execution sequence from the set of optional task execution sequences as a current task execution sequence.

[0045] The second generating module is configured to generate a current shortest path when the AGV completes the current to-be-executed tasks based on the current task execution sequence according to a preset execution scene model of the AGV, and compare the current shortest path with an existing shortest path.

[0046] The updating module is configured to, if the current shortest path is smaller than the existing shortest path, take the current shortest path as a new existing shortest path, and take the current task execution sequence as a new optimal execution sequence.

[0047] The output module is configured to delete the current task execution sequence from the set of optional task execution sequences to generate a new set of optional task execution sequences, perform the step of acquiring one task execution sequence from the set of optional task execution sequences as a current task execution sequence until the set of optional task execution sequences is empty, output the optimal execution sequence, and schedule the AGV based on the optimal execution sequence.

[0048] In addition, to achieve the above object, the present application further provides a semiconductor production material handling scheduling device, which comprises a memory, a processor and a material handling scheduling program stored in the memory and capable of running on the processor, and the material handling scheduling program realizes the steps of the above semiconductor production material handling scheduling method when executed by the processor.

[0049] In addition, to achieve the above object, the present application further provides a readable storage medium, which stores a material handling scheduling program, and the material handling scheduling program realizes the steps of the above semiconductor production material handling scheduling method when executed by a processor.

[0050] The embodiment of the present application provides a semiconductor production material handling scheduling method, device, equipment and readable storage medium. The present application generates a selectable task execution sequence set based on the current to-be-executed tasks of an AGV, wherein the current to-be-executed tasks are subtasks of the material handling tasks of the AGV; a task execution sequence is obtained from the selectable task execution sequence set as a current task execution sequence; a current shortest path is generated according to a preset execution scene model of the AGV when the AGV completes each current to-be-executed task based on the current task execution sequence, and the current shortest path is compared with an existing shortest path; if the current shortest path is smaller than the existing shortest path, the current shortest path is taken as a new existing shortest path, and the current task execution sequence is taken as a new optimal execution sequence; the current task execution sequence is deleted from the selectable task execution sequence set to generate a new selectable task execution sequence set, the step of obtaining a task execution sequence from the selectable task execution sequence set as a current task execution sequence is executed until the selectable task execution sequence set is empty, the optimal execution sequence is output, and the AGV is scheduled based on the optimal execution sequence. The present application sorts each subtask of the material handling task as the smallest task sorting unit, obtains all possible task execution sequences, and screens the optimal execution sequence from each possible task execution sequence to find the shortest path. Compared with the current scheduling mode of "task first to do", the present application is more flexible when executing the material handling task, can reduce the proportion of the empty load travel of the AGV, and improves the transportation efficiency of the AGV. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 It is the device structure schematic diagram of the hardware running environment related to the embodiment scheme of the present application.

[0052] Figure 2 It is the flowchart of the first embodiment of the semiconductor production material handling scheduling method of the present application.

[0053] Figure 3 It is the flowchart of the second embodiment of the semiconductor production material handling scheduling method of the present application.

[0054] Figure 4 It is the flowchart of the third embodiment of the semiconductor production material handling scheduling method of the present application.

[0055] Figure 5 It is the schematic diagram of a working scene of the AGV in the semiconductor production material handling scheduling method of the present application.

[0056] Figure 6 It is the schematic diagram of the Petri network model of the AGV working scene part in the semiconductor production material handling scheduling method of the present application.

[0057] Figure 7 Fig. 2 is a simulation result diagram in the semiconductor production material handling scheduling method of the present application;

[0058] Figure 8 Fig. 3 is another simulation result diagram in the semiconductor production material handling scheduling method of the present application.

[0059] The implementation, functional features and advantages of the present application will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0060] It should be understood that the specific embodiments described herein merely exemplify the application and do not limit the application.

[0061] As shown in Figure 1 , the device structure schematic diagram of the hardware running environment involved in the embodiment scheme of the present application. Figure 1 The device of the embodiment of the present application can be a PC, or a smart phone, a tablet computer, a portable computer or other electronic terminal device having data receiving, data processing and data sending functions.

[0062] As shown in

[0063] , the device can include a processor 1001 such as a CPU, a network interface 1004, a user interface 1003, a memory 1005 and a communication bus 1002. The communication bus 1002 is used to realize the connection and communication between the components. The user interface 1003 can include a display screen (Display) and an input unit such as a keyboard (Keyboard). The optional user interface 1003 can also include a standard wired interface and a wireless interface. The network interface 1004 can optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 can be a high-speed RAM memory or a stable memory (non-volatile memory) such as a magnetic disk memory. The memory 1005 can optionally also be a storage device independent of the aforementioned processor 1001. Figure 1

[0064] ​Optionally, the device can further include a camera, RF (Radio Frequency) circuit, sensors, audio circuit, WiFi module, etc. Among them, the sensors are such as light sensors, motion sensors and other sensors. Specifically, the light sensors can include ambient light sensors and proximity sensors, wherein the ambient light sensors can adjust the brightness of the display screen according to the brightness of the ambient light, and the proximity sensors can turn off the display screen and / or backlight when the mobile terminal is moved to the ear. As one of the motion sensors, the gravity acceleration sensor can detect the size of acceleration in each direction (usually three axes), and when stationary, it can detect the size and direction of gravity, which can be used for applications such as mobile terminal posture recognition (such as landscape / portrait screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc. Of course, the mobile device can also be configured with a gyroscope, barometer, hygrometer, thermometer, infrared sensor and other sensors, which will not be repeated here.

[0065] Those skilled in the art can understand that Figure 1 The terminal structure shown in the figure does not constitute a limitation on the terminal, and can include more or fewer components than the figure, or combine certain components, or different component arrangements.

[0066] As Figure 1 As shown, the memory 1005 as a computer storage readable storage medium can include an operating system, a network communication module, a user interface module, and a task execution order sorting program.

[0067] In Figure 1 In the terminal shown in the figure, the network interface 1004 is mainly used to connect to the background server and communicate data with the background server; the user interface 1003 is mainly used to connect to the client (user end) and communicate data with the client; and the processor 1001 can be used to call the task execution order sorting program stored in the memory 1005 and perform the following operations:

[0068] Generating a selectable task execution order set based on the current to-be-executed tasks of the AGV, wherein the current to-be-executed tasks are subtasks of the material handling tasks of the AGV;

[0069] Obtaining a task execution order from the selectable task execution order set as a current task execution order;

[0070] Generating a current shortest path of the AGV based on the current task execution order when completing each of the current to-be-executed tasks according to a preset execution scene model of the AGV, and comparing the current shortest path with an existing shortest path;

[0071] if the current shortest path is less than the existing shortest path, the current shortest path is taken as a new existing shortest path, and the current task execution sequence is taken as a new optimal execution sequence;

[0072] the current task execution sequence is deleted from the optional task execution sequence set to generate a new optional task execution sequence set, the step of obtaining a task execution sequence from the optional task execution sequence set as a current task execution sequence is executed until the optional task execution sequence set is empty, the optimal execution sequence is output, and the AGV is scheduled based on the optimal execution sequence.

[0073] Further, the processor 1001 can call a sorting program of a task execution sequence stored in the memory 1005, and further perform the following operations:

[0074] After the step of comparing the current shortest path with the existing shortest path, the method comprises:

[0075] if the current shortest path is greater than or equal to the existing shortest path, the existing shortest path and the optimal execution sequence remain unchanged;

[0076] The step of deleting the current task execution sequence from the optional task execution sequence set to generate a new optional task execution sequence set is executed.

[0077] Further, the processor 1001 can call a sorting program of a task execution sequence stored in the memory 1005, and further perform the following operations:

[0078] After the step of obtaining a task execution sequence from the optional task execution sequence set as a current task execution sequence, the method comprises:

[0079] It is judged whether the AGV will be overloaded when the AGV executes each current to-be-executed task based on the current task execution sequence;

[0080] if not, the step of generating a current shortest path of the AGV when the AGV executes each current to-be-executed task based on the current task execution sequence according to a preset execution scene model of the AGV is executed;

[0081] if yes, the step of deleting the current task execution sequence from the optional task execution sequence set to generate a new optional task execution sequence set is executed.

[0082] Further, the processor 1001 can call a sorting program of a task execution sequence stored in the memory 1005, and further perform the following operations:

[0083] The current tasks to be executed are picking tasks or placing tasks, and the step of judging whether the AGV will be overloaded when the AGV executes each of the current tasks to be executed based on the current task execution sequence comprises:

[0084] The execution positions where the AGV stays when the AGV executes each of the current tasks to be executed based on the current task execution sequence are obtained in sequence;

[0085] The first number of the picking tasks to be executed and the second number of the placing tasks to be executed at the execution position are obtained;

[0086] The number of the objects loaded on the AGV is obtained by subtracting the second number from the sum of the third number of the objects loaded on the AGV and the first number;

[0087] The number of the objects is compared with the preset maximum capacity of the AGV;

[0088] If there is the execution position corresponding to the number of the objects greater than the preset maximum capacity, it is determined that the AGV will be overloaded;

[0089] If there is no execution position corresponding to the number of the objects greater than the preset maximum capacity, it is determined that the AGV will not be overloaded.

[0090] Further, the processor 1001 can call the sorting program of the task execution sequence stored in the memory 1005, and further perform the following operations:

[0091] The step of generating the current shortest path of the AGV when the AGV completes each of the current tasks to be executed based on the current task execution sequence according to the preset execution scene model of the AGV comprises:

[0092] The current position of the AGV in the preset execution scene model is determined;

[0093] A preset shortest path planning algorithm is called to generate the shortest preparation path of the AGV in the preset execution scene model from the current position to the execution position of the starting point current task to be executed, wherein the starting point current task to be executed is the first current task to be executed in the current task execution sequence;

[0094] The preset shortest path planning algorithm is called to generate the shortest execution path of the AGV in the preset execution scene model when each of the current tasks to be executed is completed according to the current task execution sequence;

[0095] The shortest preparation path and the shortest execution path are added to obtain the current shortest path.

[0096] Further, the processor 1001 can invoke the sorting program of the task execution sequence stored in the memory 1005, and further perform the following operations:

[0097] The step of invoking the preset shortest path planning algorithm to generate the shortest execution path of the AGV in the preset execution scene model according to the current task execution sequence to complete each current to-be-executed task includes:

[0098] According to the current task execution sequence, each execution position of the AGV in the preset execution scene model is obtained, wherein the arrangement order of each execution position corresponds to the current task execution sequence;

[0099] The node shortest path between each adjacent execution position is obtained from the preset execution scene model;

[0100] Each node shortest path is sequentially connected and combined to obtain the shortest execution path.

[0101] Further, the processor 1001 can invoke the sorting program of the task execution sequence stored in the memory 1005, and further perform the following operations:

[0102] A set of optional task execution sequences is generated based on each current to-be-executed task of the AGV, and the method comprises:

[0103] When a new material handling task is received, the material handling task is decomposed to obtain the subtask, wherein the subtask is a picking task or a placing task;

[0104] The picking task is taken as the current to-be-executed task of the AGV;

[0105] When the picking task is executed and completed, the placing task corresponding to the picking task is taken as the current to-be-executed task.

[0106] Referring to Figure 2 , the first embodiment of the semiconductor production material handling scheduling method comprises:

[0107] Step S10, a set of optional task execution sequences is generated based on each current to-be-executed task of the AGV, wherein the current to-be-executed task is a subtask of the material handling task of the AGV;

[0108] In the embodiment, the AGV refers to an automated device for carrying objects. In the semiconductor manufacturing field, the objects carried by the AGV are wafers. Correspondingly, the workstations for storing or processing wafers in the work area where the AGV carries the wafers include machines or shelves. Therefore, the start point and the end point of the task of carrying the wafers by the AGV can be a machine (processing wafers) or a shelf (storing wafers). When the AGV carries the wafers, the AGV usually carries the wafers according to the material carrying task received by the AGV itself. The basic information of the material carrying task can include the publishing time of the task, the start point of the task, the end point of the task, and the number of the task. For example, the basic information of the material carrying task 1 is as follows: publishing time: 10:23; start point: machine A; end point: shelf B; and number: one set. It should be noted that, in actual application, when the AGV completes the material carrying task 1, the AGV needs to take one set of wafers at the machine A, and then carry the taken wafers to the shelf B and place the wafers on the shelf. Therefore, one material carrying task can actually be divided into two subtasks, i.e., a taking task and a placing task. The current task to be executed refers to the taking task or the placing task that needs to be executed by the AGV at the current time. For example, referring to FIG. 1, the AGV needs to execute a material carrying task of a wafer. The wafer is currently at a certain position (referred to as an initial position or a start point of the material carrying task). The start point can be a machine or a shelf. The AGV needs to first drive from the current position of the AGV to the start point of the material carrying task, and the driving process takes a certain time. After reaching the start point of the material carrying task, the mechanical arm of the AGV places the corresponding wafer on the AGV, and this process takes a certain time. Then, the AGV drives again, and this process takes a certain time. After reaching the destination, i.e., the end point of the material carrying task, the mechanical arm of the AGV unloads the wafer on the AGV and places the wafer at a position near the destination, and this process takes a certain time. After the unloading is completed, if the AGV still has tasks to be executed, the process is repeated until all the tasks are executed. Figure 5 FIG. 1 is a schematic diagram of a work scene of an AGV. The diagram includes nodes 1 to 17. The nodes refer to the residence points (or the execution positions in the subsequent steps) of the AGV. st1 refers to a shelf 1, st2 refers to a shelf 2, m k The machine k is indicated. The AGV will move between the nodes to perform transportation, and will reside at the residence points (nodes) to complete the taking task or the placing task on the machine or the shelf corresponding to the residence point. For example, the AGV needs to execute a material carrying task of a wafer. The wafer is currently at a certain position (referred to as an initial position or a start point of the material carrying task). The start point can be a machine or a shelf. The AGV needs to first drive from the current position of the AGV to the start point of the material carrying task, and the driving process takes a certain time. After reaching the start point of the material carrying task, the mechanical arm of the AGV places the corresponding wafer on the AGV, and this process takes a certain time. Then, the AGV drives again, and this process takes a certain time. After reaching the destination, i.e., the end point of the material carrying task, the mechanical arm of the AGV unloads the wafer on the AGV and places the wafer at a position near the destination, and this process takes a certain time. After the unloading is completed, if the AGV still has tasks to be executed, the process is repeated until all the tasks are executed.

[0109] Specifically, as an implementation form, the process of generating the set of optional task execution sequences according to the current tasks to be executed can be that all permutations of the current tasks to be executed are performed to generate all possible execution sequences of the current tasks to be executed, such as current task 1, current task 2, and current task 3, and all possible execution sequences include [1, 2, 3] (for the convenience of description, the current tasks to be executed are abbreviated, such as 1 corresponding to current task 1), [1, 3, 2], [2, 1, 3], [2, 3, 1], [3, 1, 2], and [3, 2, 1]. All possible execution sequences of the current tasks to be executed are taken as the set of optional task execution sequences.

[0110] Step S20, obtaining a task execution sequence from the set of optional task execution sequences as a current task execution sequence;

[0111] In the embodiment, the set of optional task execution sequences will be further screened to obtain an optimal task execution sequence. A task execution sequence is randomly obtained from the set of optional task execution sequences as a current task execution sequence, and the subsequent steps will test the current task execution sequence to determine the advantages and disadvantages of the current task execution sequence.

[0112] Step S30, generating a current shortest path of the AGV based on the current task execution sequence when the AGV completes the current tasks to be executed according to the preset execution scene model of the AGV, and comparing the current shortest path with an existing shortest path;

[0113] In the embodiment, the preset execution scene model of the AGV can be generated based on the actual AGV execution of the material handling task, and can describe the scene of the AGV completing the current tasks to be executed according to the current task execution sequence, so that the current shortest path corresponding to the current task execution sequence can be generated based on the preset execution scene model. The current shortest path is compared with the existing shortest path, that is, the lengths of the two paths are compared. The existing shortest path is provided with an initial value, and the initial value is infinite.

[0114] Further, the current position of the AGV in the preset execution scene model is determined, a preset shortest path planning algorithm is called to generate a shortest preparation path of the AGV in the preset execution scene model from the current position to the execution position of the starting current task to be executed, wherein the starting current task to be executed is the first current task to be executed in the current task execution sequence, the preset shortest path planning algorithm is called to generate a shortest execution path of the AGV in the preset execution scene model according to the current task execution sequence when completing the current tasks to be executed, and the shortest preparation path and the shortest execution path are added to obtain the current shortest path.

[0115] In the embodiment, the preset shortest path planning algorithm can be Dijkstra algorithm, which can solve the shortest path problem between two nodes in a directed graph or an undirected graph. The preset execution scene model can be a directed graph constructed based on an AGV working place, such as a scene model constructed based on a wafer carrying place. The current position or the execution position can be a machine or a shelf in the constructed scene model. When planning a path, the current position of the AGV in the preset execution scene model can be determined according to the actual position of the AGV in the working place, and then the shortest path between the current position and the execution position of the first current to-be-executed task in the current task execution sequence, i.e., the shortest preparation path, can be obtained by using Dijkstra algorithm. The shortest path between the execution position of the first current to-be-executed task and the execution position of the last current to-be-executed task in the current task execution sequence, i.e., the shortest execution path, can be obtained by using Dijkstra algorithm. The shortest preparation path and the shortest path are added to obtain the current shortest path corresponding to the current task execution sequence.

[0116] Further, each execution position of the AGV in the preset execution scene model is obtained according to the current task execution sequence, wherein the arrangement order of each execution position corresponds to the current task execution sequence. The node shortest path between each adjacent execution position in the preset execution scene model is obtained. The node shortest paths are sequentially connected to obtain the shortest execution path.

[0117] In the embodiment, each execution position of the AGV in the preset execution scene model is obtained according to the current task execution sequence. It should be noted that each execution position of the AGV refers to a position where the AGV needs to stay to complete each current to-be-executed task. For example, for a taking task (taking a wafer at machine A), the AGV needs to stay at machine A to perform the taking task. Correspondingly, the arrangement order of each execution position corresponds to the current task execution sequence. For example, if the current task execution sequence is a taking task 1 (staying at machine A), a taking task 2 (staying at machine B), a placing task 1 (staying at machine C), and a placing task 2 (staying at shelf A), the arrangement order of each execution position is machine A, machine B, machine C, and shelf A. Similarly, the shortest path between two adjacent execution positions, i.e., the node shortest path, is obtained by using Dijkstra algorithm. For example, the node shortest path 1 between machine A and machine B, the node shortest path 1 between machine B and machine C, and the node shortest path 3 between machine C and shelf A. The node shortest paths are sequentially connected, i.e., the node shortest path 1, the node shortest path 1, and the node shortest path 3 are sequentially connected, to obtain the shortest execution path.

[0118] In summary, the current shortest path calculation formula can be expressed as:

[0119]

[0120] In the formula, dis(x) represents the current shortest path corresponding to the current task execution order of x, AGVNowPosition represents the current position of the AGV, disDijkstr(x i ,x i+1 ) is a function, which represents the shortest distance between two points x i and x i+1 obtained by using the Dijkstra algorithm, and x i represents the execution position corresponding to the i-th current to-be-executed task in the current task execution order of x.

[0121] Step S40: If the current shortest path is less than the existing shortest path, the current shortest path is taken as a new existing shortest path, and the current task execution order is taken as a new optimal execution order.

[0122] In this embodiment, after comparing the current shortest path with the existing shortest path, if the length of the current shortest path is less than the length of the existing shortest path, it indicates that a more optimal task execution order is found, and the current shortest path at this time is taken as a new existing shortest path. Correspondingly, the current task execution order at this time is taken as a new optimal execution order, where the initial value of the optimal execution order can be set to be empty.

[0123] Further, after the step of comparing the current shortest path with the existing shortest path, the method comprises: if the current shortest path is greater than or equal to the existing shortest path, the existing shortest path and the optimal execution order are kept unchanged; and the step of deleting the current task execution order from the selectable task execution order set to generate a new selectable task execution order set is performed.

[0124] On the contrary, if the length of the current shortest path is greater than or equal to the length of the existing shortest path, it indicates that a more optimal task execution order is not found, and the existing shortest path and the optimal execution order are kept unchanged. Then, the step of deleting the current task execution order from the selectable task execution order set to generate a new selectable task execution order set is performed.

[0125] Step S50, deleting the current task execution sequence from the optional task execution sequence set to generate a new optional task execution sequence set, performing the step of obtaining a task execution sequence from the optional task execution sequence set as the current task execution sequence until the optional task execution sequence set is empty, outputting the optimal execution sequence, and scheduling the AGV based on the optimal execution sequence.

[0126] In the embodiment, the optimal execution sequence is obtained by comparing each element (each task execution sequence) in the optional task execution sequence set, so after obtaining the comparison result of the current shortest path and the existing shortest path, the current task execution sequence is deleted from the optional task execution sequence set to generate a new optional task execution sequence set, thereby avoiding repeated comparison of the elements in the optional task execution sequence set. If the new optional task execution sequence set is not an empty set, the step of obtaining a task execution sequence from the optional task execution sequence set as the current task execution sequence will continue, that is, it is determined whether the new current task execution sequence can be the optimal execution sequence. Otherwise, if the optional task execution sequence set is an empty set, it means that each task execution sequence has been judged, and the optimal execution sequence at this time is outputted. That is, the loop process of judging the optimal execution sequence will continue until the optional task execution sequence set becomes an empty set. At this time, the optimal task execution sequence of the AGV has been obtained, and the AGV carrying the material can be scheduled based on the optimal task execution sequence to improve the carrying efficiency of the AGV. It can be understood that, in the embodiment, compared with the current scheduling mode of "task first to first do", since the task sorting is based on the sorting of the sub-tasks of each material carrying task, the AGV is more flexible when executing the task. For example, if the scheduling mode of "task first to first do" is adopted, when the AGV receives the material carrying task 1, the AGV will execute the picking task 1 of the material carrying task 1 and then execute the placing task 1 of the material carrying task 1, that is, the AGV will complete other material carrying tasks after completing the material carrying task 1. If the sorting method of the present application is adopted, when the AGV reaches the execution position of the picking task 1 of the material carrying task 1, in addition to executing the material carrying task 1, the AGV can also execute the sub-tasks of other material carrying tasks that need to be executed at the execution position. Therefore, the present application can reduce the proportion of empty travel of the AGV and improve the transportation efficiency of the AGV.

[0127] To further illustrate the beneficial effects of the present application, the semiconductor production material handling scheduling method of the present application and the current existing "first come first served" scheduling method are simulated respectively. The Petri network model (Resource-Oriented Petri Net, ROPN) of the AGV working scene is constructed. The circles represent the library, which represents the resource state or operation; the transitions are represented by rectangular boxes, which are used to describe the start and end of events, to determine the local state and the occurrence of events, so that the system is transferred from a discrete state to another discrete state; the directed arcs are used to connect the library and the transition; the tokens represent the dynamic objects in the library, which can be moved from one library to another. The Petri network model is relatively mature at present, so it is not described here. As shown in Figure 6 , it is a schematic diagram of the Petri network model of the AGV working scene. In the figure, the library P i represents the residence point i of the AGV, the transition (t i,j ) represents the movement of the AGV from the residence point i to j, the time (d i,j ) represents the time of the AGV moving from i to j, the time d k represents the residence time of the AGV at k, and the AGV is the token. Different task amounts per hour are set, such as 13, 15, 22 and 27, and the simulation results of the above two methods are obtained respectively. As shown in Figure 7 and Figure 8 , method 1 is the semiconductor production material handling scheduling method of the present application, and method 2 is the current existing "first come first served" scheduling method. As shown in Figure 7 , the unit of downtime is: hour, the unit of working time is: hour, the utilization rate is the ratio of working time to total time, the total time is the sum of working time and downtime, and the task amount is: pieces / hour. As shown in Figure 7 , it can be seen that under the same sorting method, as the task amount increases, the downtime decreases, the working time increases, and the utilization rate increases. Among them, in the case of task amount of 22 and 27, the working time of AGV under method 1 is less than that under method 2, which shows that method 1 is beneficial to reduce the working time. Further, as shown in Figure 8 , the unit of task average waiting time is: second, the unit of task minimum waiting time is: second, and the unit of task maximum waiting time is: second. As shown in Figure 8 , it can be seen that in the case of task amount of 22 and 27, the task average waiting time of method 1 is less than that of method 2, so the semiconductor production material handling scheduling method of the present application can improve the transportation efficiency of AGV.

[0128] In the embodiment, a set of optional task execution sequences is generated based on each current to-be-executed task of the AGV, wherein the current to-be-executed task is a subtask of the AGV material handling task; one task execution sequence is obtained from the set of optional task execution sequences as a current task execution sequence; a current shortest path is generated according to a preset execution scene model of the AGV when the AGV completes each current to-be-executed task based on the current task execution sequence, the current shortest path is compared with an existing shortest path; if the current shortest path is smaller than the existing shortest path, the current shortest path is taken as a new existing shortest path, and the current task execution sequence is taken as a new optimal execution sequence; the current task execution sequence is deleted from the set of optional task execution sequences to generate a new set of optional task execution sequences, the step of obtaining one task execution sequence from the set of optional task execution sequences as a current task execution sequence is executed until the set of optional task execution sequences is empty, and the optimal execution sequence is output. The present application sorts each subtask of the material handling task as the smallest task sorting unit, obtains all possible task execution sequences, and screens the optimal execution sequence from each possible task execution sequence with the goal of finding the shortest path. Compared with the current scheduling mode of "task first to do first", the present application is more flexible when executing the material handling task, can reduce the proportion of empty load travel of the AGV, and improves the transportation efficiency of the AGV.

[0129] Further, referring to Figure 3 Based on the first embodiment of the semiconductor production material handling scheduling method, the second embodiment of the semiconductor production material handling scheduling method is proposed.

[0130] After the step of obtaining one task execution sequence from the set of optional task execution sequences as a current task execution sequence, the method comprises:

[0131] In step S210, it is judged whether the AGV will be overloaded when the AGV executes each current to-be-executed task based on the current task execution sequence;

[0132] Further, the execution positions where the AGV stays when executing each of the current tasks to be executed based on the current task execution sequence are acquired in sequence; the first number of the pickup tasks that need to be executed and the second number of the placement tasks that need to be executed at the execution positions are acquired; the third number of the articles already loaded on the AGV is subtracted from the sum of the first number and the second number to obtain the number of articles loaded on the AGV at the execution positions; the number of articles is compared with the preset maximum capacity of the AGV; if there is an execution position corresponding to the number of articles greater than the preset maximum capacity, it is determined that the AGV will be overloaded; if there is no execution position corresponding to the number of articles greater than the preset maximum capacity, it is determined that the AGV will not be overloaded.

[0133] In the present embodiment, it needs to be explained that, due to the limitation of the structure of the AGV, the number of wafers that can be loaded by an AGV is limited, so not all of the task execution sequences in the generated collection of optional task execution sequences are feasible, that is, when the AGV executes each of the current tasks to be executed under a part of the task execution sequences, if the AGV is overloaded, the AGV will not be able to continue to execute the following tasks to be executed. For example, the maximum capacity of a wafer of an AGV is 4, if the AGV needs to continuously execute 5 pickup tasks according to the current task execution sequence, the AGV has been fully loaded after executing 4 pickup tasks, so the AGV cannot continue to execute the 5th pickup task.

[0134] The execution positions are sequentially obtained when the AGV executes each of the current tasks to be executed based on the current task execution sequence. Similarly, the execution position can be a position where the AGV needs to stay in a preset execution scene model when the AGV executes the current task to be executed. Further, the first number of the picking tasks and the second number of the placing tasks that need to be executed at the execution position are obtained. For example, when the AGV executes the first current task to be executed in the current task execution sequence, the AGV stays at the execution position 1. If the current task execution sequence is executed at the execution position 1, a plurality of current tasks to be executed, including picking tasks and placing tasks, can be executed. The picking task can pick the wafer from the machine or the shelf corresponding to the execution position 1 to the AGV, and the number of wafers loaded on the AGV increases. The placing task can place the wafer from the AGV on the machine or the shelf corresponding to the execution position 1, and the number of wafers loaded on the AGV decreases. It can be understood that after the first number of the picking tasks and the second number of the placing tasks executed at the execution position 1 are determined, the number of wafers that the AGV needs to load after executing all the tasks at the execution position 1 (each picking and placing is a group of wafers) can be determined, that is, the third number of wafers currently loaded on the AGV is added to the first number and then the second number is subtracted to obtain the number of wafers (i.e., the number of objects) that the AGV needs to load at the execution position 1, that is, the number of objects = the third number + the first number - the second number. The number of objects is compared with the preset maximum capacity of the AGV, wherein the preset maximum capacity of the AGV can be set according to the AGV itself, which indicates the maximum number of wafers that the AGV can load.

[0135] The number of objects at the execution position is sequentially compared with the preset maximum capacity of the AGV. If there is or there appears an execution position where the number of objects is greater than the preset maximum capacity of the AGV, it can be determined that the AGV will be overloaded. Conversely, if the number of objects at all execution positions is less than or equal to the preset maximum capacity of the AGV, it is determined that the AGV will not be overloaded.

[0136] If the AGV will not be overloaded, the step of generating the current shortest path of the AGV when executing each of the current tasks to be executed based on the current task execution sequence according to the preset execution scene model of the AGV is executed.

[0137] Specifically, if the AGV will not be overloaded, it indicates that the task execution sequence is feasible, but it is not necessarily the best execution sequence, so the step of generating the current shortest path of the AGV when executing each of the current tasks to be executed based on the current task execution sequence according to the preset execution scene model of the AGV is continued.

[0138] If the AGV will be overloaded, the step of deleting the current task execution sequence from the optional task execution sequence set and generating a new optional task execution sequence set is performed.

[0139] Specifically, if the AGV will be overloaded, it indicates that the task execution sequence is not feasible, and thus the step of deleting the current task execution sequence from the optional task execution sequence set and generating a new optional task execution sequence set is performed.

[0140] It can be understood that in the embodiment, the optional task execution sequence set is preliminarily screened, and the task execution sequence that cannot be completed is eliminated in advance, so as to avoid the situation that the AGV cannot execute the task.

[0141] Further, referring to Figure 4 , the third embodiment of the semiconductor production material handling scheduling method is proposed based on the first embodiment of the semiconductor production material handling scheduling method.

[0142] Before the step of generating an optional task execution sequence set based on each current to-be-executed task of the AGV, the method comprises:

[0143] Step S01, when a new material handling task is received, the material handling task is decomposed to obtain the sub-tasks, wherein the sub-tasks are taking tasks or placing tasks;

[0144] Step S02, taking the taking task as the current to-be-executed task of the AGV;

[0145] Step S03, when the taking task is executed, the placing task corresponding to the taking task is taken as the current to-be-executed task.

[0146] In this embodiment, upon receiving a new material handling task, the task is decomposed into subtasks. A single material handling task can be decomposed into two subtasks: a pick-up task and a placement task. The pick-up task is prioritized as the AGV's current task to be executed and included in the generation of the optional task execution order set. Once the pick-up task is completed, the corresponding placement task is then added as the current task to be executed and included in the generation of the optional task execution order set. This avoids having both the pick-up and placement tasks of a material handling task simultaneously in the generation of the optional task execution order set. It is understood that the placement task of a material handling task must be completed after the pick-up task is completed. If the placement task of the same material handling task appears before the pick-up task in the task execution order, the AGV will be unable to execute the task correctly. Therefore, in this embodiment, the pick-up task is prioritized as the AGV's current task to be executed and included in the task sorting. Only after the pick-up task is completed is the corresponding placement task included in the sorting. This reduces the number of unexecutable task execution sequences.

[0147] Furthermore, embodiments of the present invention also propose a semiconductor manufacturing material handling and scheduling device, the semiconductor manufacturing material handling and scheduling device comprising:

[0148] The first generation module is used to generate a set of optional task execution orders based on each currently pending task of the AGV, wherein the currently pending task is a sub-task of the material handling task of the AGV;

[0149] The acquisition module is used to acquire a task execution order from the set of optional task execution orders as the current task execution order;

[0150] The second generation module is used to generate the current shortest path when the AGV completes each of the currently pending tasks based on the current task execution order according to the preset execution scenario model of the AGV, and compare the current shortest path with the existing shortest path;

[0151] The update module is used to, if the current shortest path is less than the existing shortest path, use the current shortest path as the new existing shortest path and use the current task execution order as the new best execution order.

[0152] The output module is used to delete the current task execution order from the set of optional task execution orders to generate a new set of optional task execution orders, perform the step of obtaining a task execution order from the set of optional task execution orders as the current task execution order, until the set of optional task execution orders is empty, output the optimal execution order, and schedule the AGV based on the optimal execution order.

[0153] Optionally, the second generating module is further configured to:

[0154] if the current shortest path is greater than or equal to the existing shortest path, maintaining the existing shortest path and the optimal execution order unchanged;

[0155] performing the step of deleting the current task execution order from the optional task execution order set to generate a new optional task execution order set.

[0156] Optionally, the semiconductor production material handling scheduling device further comprises a judging module, and the judging module is configured to:

[0157] judge whether the AGV will be overloaded when the AGV executes each of the current to-be-executed tasks based on the current task execution order;

[0158] if not, performing the step of generating the current shortest path of the AGV when the AGV executes each of the current to-be-executed tasks based on the current task execution order according to the preset execution scene model of the AGV;

[0159] if yes, performing the step of deleting the current task execution order from the optional task execution order set to generate a new optional task execution order set.

[0160] Optionally, the current to-be-executed task is a picking task or a placing task, and the judging module is further configured to:

[0161] sequentially obtaining execution positions at which the AGV stays when the AGV executes each of the current to-be-executed tasks based on the current task execution order;

[0162] obtaining a first quantity of picking tasks that need to be executed and a second quantity of placing tasks that need to be executed at the execution positions;

[0163] obtaining a quantity of objects loaded on the AGV at the execution positions by subtracting the second quantity from a sum of the first quantity and a third quantity of objects already loaded on the AGV;

[0164] comparing the quantity of objects with a preset maximum capacity of the AGV;

[0165] if there is an execution position corresponding to the quantity of objects that is greater than the preset maximum capacity, determining that the AGV will be overloaded;

[0166] if there is no execution position corresponding to the quantity of objects that is greater than the preset maximum capacity, determining that the AGV will not be overloaded.

[0167] Optionally, the second generating module is further configured to:

[0168] determine a current position of the AGV in the preset execution scene model;

[0169] invoke a preset shortest path planning algorithm to generate a shortest preparation path of the AGV in the preset execution scene model from the current position to a starting point of a current to-be-executed task in the current task execution sequence;

[0170] invoke the preset shortest path planning algorithm to generate a shortest execution path of the AGV in the preset execution scene model when completing each current to-be-executed task in the current task execution sequence;

[0171] add the shortest preparation path and the shortest execution path to obtain the current shortest path.

[0172] Optionally, the second generating module is further configured to:

[0173] obtain each execution position of the AGV in the preset execution scene model according to the current task execution sequence, wherein an arrangement order of each execution position corresponds to the current task execution sequence;

[0174] obtain a node shortest path between each adjacent execution position from the preset execution scene model;

[0175] sequentially connect and combine each node shortest path to obtain the shortest execution path.

[0176] Optionally, the first generating module is further configured to:

[0177] when receiving a new material handling task, decompose the material handling task to obtain the subtask, wherein the subtask is a picking task or a placing task;

[0178] take the picking task as the current to-be-executed task of the AGV;

[0179] when the picking task is executed and completed, take the placing task corresponding to the picking task as the current to-be-executed task.

[0180] The semiconductor production material carrying scheduling device provided by the present application adopts the semiconductor production material carrying scheduling method in the above embodiment, and aims to solve the technical problem that the current AGV carrying efficiency is low, which affects the overall efficiency of wafer production. Compared with the prior art, the semiconductor production material carrying scheduling device provided by the embodiment of the present application has the same beneficial effects as the semiconductor production material carrying scheduling method provided by the above embodiment, and other technical features in the semiconductor production material carrying scheduling device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0181] In addition, the embodiment of the present application also provides a semiconductor production material carrying scheduling device, which comprises a memory, a processor and a material carrying scheduling program stored in the memory and executable on the processor. The material carrying scheduling program is executed by the processor to realize the steps of the semiconductor production material carrying scheduling method as described above.

[0182] The specific implementation of the semiconductor production material carrying scheduling device of the present application is basically the same as the above-mentioned material carrying scheduling method, which will not be repeated here.

[0183] In addition, the embodiment of the present application also provides a readable storage medium, which stores a material carrying scheduling program. The material carrying scheduling program is executed by a processor to realize the steps of the semiconductor production material carrying scheduling method as described above.

[0184] The specific implementation of the readable storage medium of the present application is basically the same as the above-mentioned semiconductor production material carrying scheduling method, which will not be repeated here.

[0185] It should be noted that in this paper, the term "including", "containing" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or system including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes elements inherent to such process, method, article or system. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or system including the element.

[0186] The above-mentioned embodiment number of the present application is only for description, not representing the advantages and disadvantages of the embodiment.

[0187] Those skilled in the art can clearly understand the above-mentioned embodiment method can be realized by means of software and the necessary general hardware platform, of course, also can be through hardware, but in many cases the former is the better embodiment. Based on such understanding, the technical solutions of the present application essentially or say the part of the contribution to the prior art can be embodied in the form of software products, the computer software product is stored in a storage medium (such as ROM / RAM, magnetic disc, optical disc) as described above, including a number of instructions to make a terminal device (may be a mobile phone, computer, server, or network equipment, etc.) executes the method described in various embodiments of the present application.

[0188] The above is only the preferred embodiment of the present application, not therefore limit the patent scope of the present application, any equivalent structure or equivalent flow transformation made by using the content of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A semiconductor production material handling scheduling method characterized by, The semiconductor production material handling scheduling method comprises the following steps: generating a set of optional task execution sequences based on each current to-be-executed task of the AGV, wherein the current to-be-executed task is a subtask of the material handling task of the AGV; obtaining a task execution sequence from the set of optional task execution sequences as a current task execution sequence; generating a current shortest path of the AGV based on the current task execution sequence according to a preset execution scenario model of the AGV when each current to-be-executed task is completed, comparing the current shortest path with an existing shortest path; if the current shortest path is smaller than the existing shortest path, taking the current shortest path as a new existing shortest path and taking the current task execution sequence as a new optimal execution sequence; deleting the current task execution sequence from the set of optional task execution sequences to generate a new set of optional task execution sequences, executing the step of obtaining a task execution sequence from the set of optional task execution sequences as a current task execution sequence until the set of optional task execution sequences is empty, outputting the optimal execution sequence, and scheduling the AGV based on the optimal execution sequence.

2. The semiconductor production material handling scheduling method according to Claim 1, wherein, After the step of comparing the current shortest path with the existing shortest path, the method comprises: if the current shortest path is greater than or equal to the existing shortest path, keeping the existing shortest path and the optimal execution sequence unchanged; executing the step of deleting the current task execution sequence from the set of optional task execution sequences to generate a new set of optional task execution sequences.

3. The semiconductor production material handling scheduling method according to Claim 1, wherein, After the step of obtaining a task execution sequence from the set of optional task execution sequences as a current task execution sequence, the method comprises: judging whether the AGV will be overloaded when each current to-be-executed task is executed based on the current task execution sequence; if not, executing the step of generating a current shortest path of the AGV based on the current task execution sequence according to a preset execution scenario model of the AGV when each current to-be-executed task is completed; if yes, executing the step of deleting the current task execution sequence from the set of optional task execution sequences to generate a new set of optional task execution sequences.

4. The semiconductor production material handling scheduling method according to Claim 3, wherein, The current to-be-executed task is a picking task or a placing task, and the step of judging whether the AGV will be overloaded when each current to-be-executed task is executed based on the current task execution sequence comprises: obtaining execution positions of the AGV based on the current task execution sequence when each current to-be-executed task is executed in sequence; obtaining a first number of picking tasks to be executed and a second number of placing tasks to be executed at the execution positions; obtaining a number of objects to be loaded on the AGV at the execution positions by subtracting the second number from a sum of the first number and a third number of objects already loaded on the AGV; comparing the number of objects with a preset maximum capacity of the AGV; and if the number of objects is greater than the preset maximum capacity, determining that the AGV will be overloaded. If the number of the objects corresponding to the execution position is greater than the preset maximum capacity, it is determined that the AGV will be overloaded. If the number of the objects corresponding to the execution position is not greater than the preset maximum capacity, it is determined that the AGV will not be overloaded.

5. The semiconductor production material handling scheduling method according to Claim 1, wherein, The step of generating the current shortest path of the AGV based on the current task execution sequence according to the preset execution scene model of the AGV comprises: determining the current position of the AGV in the preset execution scene model; calling a preset shortest path planning algorithm to generate a shortest preparation path of the AGV in the preset execution scene model from the current position to the execution position of the starting point current task to be executed, wherein the starting point current task to be executed is the first current task to be executed in the current task execution sequence; calling the preset shortest path planning algorithm to generate a shortest execution path of the AGV in the preset execution scene model when completing each current task to be executed in the current task execution sequence; adding the shortest preparation path and the shortest execution path to obtain the current shortest path.

6. The semiconductor production material handling scheduling method according to Claim 5, wherein, The step of calling the preset shortest path planning algorithm to generate the shortest execution path of the AGV in the preset execution scene model when completing each current task to be executed in the current task execution sequence comprises: obtaining each execution position of the AGV in the preset execution scene model according to the current task execution sequence, wherein the arrangement order of each execution position corresponds to the current task execution sequence; obtaining the node shortest path between each adjacent execution position from the preset execution scene model; sequentially connecting and combining each node shortest path to obtain the shortest execution path.

7. The semiconductor production material handling scheduling method according to Claim 1, wherein, The method comprises: when a new material handling task is received, decomposing the material handling task to obtain a subtask, wherein the subtask is a picking task or a placing task; taking the picking task as the current task to be executed of the AGV; when the picking task is executed and completed, taking the placing task corresponding to the picking task as the current task to be executed.

8. A semiconductor production material handling scheduling apparatus characterized by comprising: The semiconductor production material handling scheduling device comprises: a first generation module configured to generate a set of optional task execution sequences based on each current task to be executed of an AGV, wherein the current task to be executed is a subtask of a material handling task of the AGV; an acquisition module configured to acquire one task execution sequence from the set of optional task execution sequences as a current task execution sequence; a second generation module configured to generate a current shortest path of the AGV based on the current task execution sequence according to a preset execution scene model of the AGV, and compare the current shortest path with an existing shortest path. An updating module is configured to, if the current shortest path is shorter than the existing shortest path, take the current shortest path as a new existing shortest path, and take the current task execution sequence as a new optimal execution sequence. An output module is configured to delete the current task execution sequence from the set of optional task execution sequences to generate a new set of optional task execution sequences, execute the step of obtaining a task execution sequence from the set of optional task execution sequences as a current task execution sequence until the set of optional task execution sequences is empty, output the optimal execution sequence, and schedule the AGV based on the optimal execution sequence.

9. A semiconductor production material handling scheduling apparatus characterized by comprising: The semiconductor production material handling scheduling device comprises a memory, a processor, and a material handling scheduling program stored on the memory and executable on the processor, and the material handling scheduling program, when executed by the processor, implements the steps of the semiconductor production material handling scheduling method according to any one of claims 1 to 7.

10. A readable storage medium, characterized by, The readable storage medium stores a material handling scheduling program, and the material handling scheduling program, when executed by the processor, implements the steps of the semiconductor production material handling scheduling method according to any one of claims 1 to 7.

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