Intelligent trolley scheduling method for production line
By calculating the maximum process capacity of the intelligent vehicle and the production line cycle time, the number of intelligent vehicles is dynamically scheduled, solving the problem that a fixed number of vehicles cannot adapt to changes in cycle time and achieving efficient utilization of resources.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SAIC GM WULING AUTOMOBILE CO LTD
- Filing Date
- 2025-12-16
- Publication Date
- 2026-05-08
AI Technical Summary
In existing technologies, a fixed number of intelligent vehicles cannot adapt to changes in production cycle on an automobile production line, leading to insufficient transportation demand or waste of resources.
By calculating the maximum process capacity of a single intelligent vehicle based on multiple nodes of the production line, and combining the preset operating rate and the production line cycle time to dynamically schedule the number of intelligent vehicles, the number of intelligent vehicles on the production line can be flexibly adjusted according to the cycle time.
The system enables dynamic control of the number of intelligent vehicles, which can meet transportation needs while avoiding idleness and improve resource utilization efficiency.
Smart Images
Figure CN121998293A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of automated logistics and intelligent manufacturing technology, specifically relating to an intelligent vehicle scheduling method for a production line. Background Technology
[0002] As the automotive manufacturing industry accelerates its transformation towards intelligence and flexibility, the logistics efficiency and production collaboration capabilities of automotive production lines directly impact the cycle time and quality of vehicle manufacturing. In recent years, intelligent vehicles, as a new generation of unmanned material handling equipment, have achieved trackless operation through laser SLAM or visual navigation, possessing the capabilities of autonomous path planning, multi-vehicle collaborative scheduling, and seamless integration with MES systems.
[0003] In the existing technology, some companies have tried to use a fixed number of intelligent vehicles for transportation tasks on the production line. However, since the pace of the automobile production line is sometimes adjusted and changed, when the pace is faster, a fixed number of intelligent vehicles cannot meet the transportation needs and affect the final assembly progress. When the pace is slower, a fixed number of intelligent vehicles will be idle, wasting resources. Summary of the Invention
[0004] To address this issue, the present invention provides a method for scheduling intelligent vehicles on a production line, thereby solving the problem in the prior art where a fixed number of intelligent vehicles are used for transportation tasks on the production line, resulting in unmet transportation needs or wasted transportation resources due to changes in the production cycle.
[0005] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for scheduling intelligent vehicles on a production line, comprising: The maximum process capacity of a single intelligent vehicle is obtained based on multiple nodes of the production line; the maximum process capacity is the time taken for a single intelligent vehicle to complete one cycle through all nodes of the production line. The stable process capability of a single intelligent vehicle is obtained based on the preset operating rate and the maximum process capability of a single intelligent vehicle. The number of intelligent vehicles on the production line is determined based on the production line cycle time and the stable process capability of a single intelligent vehicle. The target number of intelligent vehicles is determined based on the number of online intelligent vehicles. The intelligent vehicles are scheduled according to the target number of intelligent vehicles, so that the number of intelligent vehicles on the production line is the target number of intelligent vehicles.
[0006] Furthermore, the step of obtaining the stable process capability of a single intelligent vehicle based on the preset operating rate and the maximum process capability of a single intelligent vehicle includes: Based on the preset operating rate and the maximum process capacity of a single intelligent vehicle, the stable process capacity of a single intelligent vehicle is obtained through the first formula, which is: T稳定 = T 最大 ×O 预设 ; Among them, T 稳定 To ensure stable process capabilities for a single intelligent vehicle, T 最大 For the maximum process capability of a single intelligent vehicle, O 预设 The preset operating rate.
[0007] Furthermore, the determination of the number of intelligent vehicles on the production line based on the production line cycle time and the stable process capability of a single intelligent vehicle includes: The production line cycle time is acquired in real time; the cycle time is a flexible cycle time that changes constantly. The number of intelligent vehicles on the production line is obtained using a second formula based on the production line cycle time and the stable process capability of a single intelligent vehicle; the second formula is: N = T 稳定 / T 节拍 ; Where N represents the number of online smart cars, T 稳定 To ensure stable process capabilities for a single intelligent vehicle, T 节拍 This refers to the time consumed per unit, calculated based on the production line cycle time.
[0008] Furthermore, the method of obtaining the maximum process capability of a single intelligent vehicle based on multiple nodes of the production line includes: The production line includes multiple nodes with fixed time consumption and nodes with travel time consumption; the time consumption of the fixed time consumption node is a preset fixed time consumption, and the time consumption of the travel time consumption node is the travel time consumption. The maximum process capacity of a single intelligent vehicle is obtained by adding the time consumed at each fixed time-consuming node in the production line to the time consumed at each driving time-consuming node.
[0009] Furthermore, the step of adding the time consumed at each fixed time-consuming node in the production line to the time consumed at each travel time-consuming node to obtain the maximum process capacity of the single intelligent vehicle includes: When the production line is a door assembly line, the fixed time-consuming nodes include the door disassembly node, the waiting-to-feed node, the waiting-to-receive node, the waiting-to-warehouse node, the waiting-to-install node, and the installation node; the travel time-consuming nodes include the first operating section, the feeding section, the second operating section, the third operating section, the warehousing operating section, the warehouse adjustment operating section, the outbound operating section, the fourth operating section, and the fifth operating section. The maximum process capacity of a single intelligent vehicle is obtained by adding up the time consumed at each node in the door assembly line.
[0010] Furthermore, the time consumed by the door dismantling node, the waiting for material release node, the waiting for material receiving node, the waiting for warehousing node, the waiting for installation node, and the installation node are all preset fixed values.
[0011] Furthermore, the method also includes: Based on the first preset speed and the lengths of the first operating segment, the inbound operating segment, the transfer operating segment, the outbound operating segment, and the fourth operating segment, the travel time of the first operating segment, the inbound operating segment, the transfer operating segment, the outbound operating segment, and the fourth operating segment are obtained in sequence through the time calculation formula. The travel time of the material discharge section is obtained by using the time calculation formula based on the second preset speed and the length of the material discharge section. Based on the third preset speed and the lengths of the second, third, and fifth operating segments, the travel time for the second, third, and fifth operating segments is obtained sequentially using the time calculation formula.
[0012] Furthermore, the time consumption calculation formula is as follows: T 耗时 = L / V; Among them, T 耗时 For the corresponding travel time L, L is the length of the first operating section, the material feeding section, the second operating section, the third operating section, the warehousing operating section, the warehousing adjustment operating section, the warehousing operating section, the fourth operating section, or the fifth operating section; V is the first preset speed, the second preset speed, or the third preset speed corresponding to L.
[0013] Furthermore, determining the target number of intelligent vehicles based on the number of online intelligent vehicles includes: Obtain the number of workstations on the production line; Multiply the number of workstations by the preset number of carts per workstation to obtain the number of intelligent carts at each workstation. The target number of intelligent vehicles is obtained by adding the number of intelligent vehicles at the workstation, the preset redundancy number, and the number of intelligent vehicles on the line.
[0014] Further, the step of scheduling intelligent vehicles according to the target number of intelligent vehicles, so that the number of intelligent vehicles on the production line is the target number of intelligent vehicles, includes: When the number of intelligent vehicles actually running on the production line is less than the target number of intelligent vehicles, n idle intelligent vehicles outside the production line are scheduled to be incorporated into the production line, where n = target number of intelligent vehicles - number of intelligent vehicles actually running on the production line. When the number of smart cars actually running on the production line is higher than the target number of smart cars, the smart cars actually running on the production line are sorted from low to high battery level, and the first n smart cars are controlled to leave the production line and go to the charging station for charging, where n = the number of smart cars actually running on the production line - the target number of smart cars.
[0015] Secondly, this application also proposes an intelligent vehicle scheduling system for a production line, the system comprising: The process capability module is used to obtain the maximum process capability of a single intelligent vehicle based on multiple nodes of the production line; the maximum process capability is the time taken for a single intelligent vehicle to complete one cycle through all nodes of the production line; and the stable process capability of a single intelligent vehicle is obtained based on the preset operating rate and the maximum process capability of the single intelligent vehicle. The vehicle quantity module is used to obtain the number of intelligent vehicles on the production line based on the production line cycle time and the stable process capability of a single intelligent vehicle; and to determine the target number of intelligent vehicles based on the number of intelligent vehicles on the production line. The scheduling module is used to schedule intelligent vehicles according to the target number of intelligent vehicles, so that the number of intelligent vehicles on the production line is the target number of intelligent vehicles.
[0016] The present invention, by adopting the above technical solution, has at least the following beneficial effects: This invention provides a method for scheduling intelligent vehicles on a production line. The method obtains the maximum process capacity of a single intelligent vehicle based on multiple nodes of the production line, determines the stable process capacity of a single intelligent vehicle based on a preset operating rate and the maximum process capacity, and calculates the number of intelligent vehicles on the production line based on the production line cycle time and the stable process capacity of a single intelligent vehicle. The method then controls the number of intelligent vehicles on the production line in real time through a scheduling system based on the number of intelligent vehicles on the production line. This invention combines each node of the production line with the cycle time, enabling the number of intelligent vehicles on the production line to be dynamically adjusted according to the flexible changes in the cycle time. This maintains a reasonable number of intelligent vehicles on the production line, which can both complete the transportation tasks on the line and effectively avoid the waste of transportation resources caused by idle intelligent vehicles.
[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description
[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1 This is a flowchart illustrating an exemplary embodiment of the present invention of a method for scheduling intelligent vehicles on a production line; Figure 2 This is a schematic diagram of the various nodes of the door assembly line shown in an exemplary embodiment of the present invention; Figure 3 This is a schematic block diagram illustrating an intelligent vehicle scheduling system for a production line, as shown in an exemplary embodiment of the present invention.
[0020] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. Detailed Implementation
[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be described in detail below. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other implementation methods obtained by those skilled in the art without creative effort are within the scope of protection of this invention.
[0022] In existing technologies, some companies attempt to use a fixed number of intelligent vehicles for transportation tasks on the production line. However, since the cycle time on the automobile production line sometimes changes, when the cycle time is faster, a fixed number of intelligent vehicles cannot meet the transportation needs and affect the final assembly schedule. When the cycle time is slower, a fixed number of intelligent vehicles will be idle, wasting resources. The intelligent vehicles can be IGVs or AGVs; that is, Intelligent Guided Vehicles (IGVs) and Automated Guided Vehicles (AGVs).
[0023] This invention provides a method for scheduling intelligent vehicles on a production line. By combining each node of the production line with the cycle time, the number of intelligent vehicles on the production line can be dynamically adjusted according to the flexible changes in the cycle time, so that the number of intelligent vehicles on the production line is kept at a reasonable level. This method can not only complete the transportation tasks on the line, but also effectively avoid the waste of transportation resources caused by idle intelligent vehicles.
[0024] The method of the present invention will be described below through specific embodiments.
[0025] Please see Figure 1 , Figure 1 This is a flowchart illustrating an exemplary embodiment of the present invention of a smart car scheduling method for a production line. See also: Figure 1 The method includes: Step S11: Obtain the maximum process capacity of a single intelligent vehicle based on multiple nodes of the production line; the maximum process capacity is the time taken for a single intelligent vehicle to complete one cycle through all nodes of the production line. Step S12: Obtain the stable process capability of a single intelligent vehicle based on the preset operating rate and the maximum process capability of a single intelligent vehicle. Step S13: Obtain the number of intelligent vehicles on the production line based on the production line cycle time and the stable process capability of a single intelligent vehicle. Step S14: Determine the target number of smart cars based on the number of online smart cars; Step S15: Schedule the intelligent vehicles according to the target number of intelligent vehicles, so that the number of intelligent vehicles on the production line is the target number of intelligent vehicles.
[0026] It should be noted that the technical solution provided in this embodiment can be used in practice as a mini-program or a plugin within an existing production scheduling system, or as a standalone application that implements scheduling functions through external interfaces. Applicable scenarios include, but are not limited to, intelligent vehicle scheduling on production lines.
[0027] It should be noted that this method yields the target number of intelligent vehicles. Based on the target number of intelligent vehicles and the actual number of intelligent vehicles on the production line, the existing scheduling system is used to further control the intelligent vehicles to enter or leave the production line.
[0028] It should be noted that the number of online smart cars is the minimum number of smart cars that need to be running on the production line under the current production line cycle time.
[0029] It is understood that the method provided in this embodiment obtains the maximum process capacity of a single intelligent vehicle based on multiple nodes of the production line, obtains the stable process capacity of a single intelligent vehicle based on the preset operating rate and the maximum process capacity of a single intelligent vehicle, obtains the number of intelligent vehicles on the production line based on the production line cycle time and the stable process capacity of a single intelligent vehicle, and controls the number of intelligent vehicles on the production line in real time through a scheduling system based on the number of intelligent vehicles on the production line. In this application, each node of the production line is combined with the cycle time, so that the number of intelligent vehicles on the production line can be dynamically adjusted with the flexible changes of the cycle time, so that the number of intelligent vehicles on the production line is kept at a reasonable level, which can not only complete the transportation tasks on the line, but also effectively avoid the waste of transportation resources caused by idle intelligent vehicles.
[0030] In practice, step S11, "obtaining the maximum process capability of a single intelligent vehicle based on multiple nodes of the production line", includes: adding the time consumed by each node in the production line to obtain the maximum process capability of a single intelligent vehicle.
[0031] Specifically, the production line has multiple nodes including fixed time-consuming nodes and travel time-consuming nodes; the time consumed by the fixed time-consuming nodes is a preset fixed time, and the time consumed by the travel time-consuming nodes is the travel time; the maximum process capacity of a single intelligent vehicle is obtained by adding the time consumed by each fixed time-consuming node and the time consumed by each travel time-consuming node in the production line.
[0032] It should be noted that the preset fixed time for each fixed time node is set based on the historical time data of the corresponding node. For example, if the historical time for waiting for the installation node includes 10 seconds, 12 seconds and 14 seconds, then the preset fixed time for waiting for the installation node is: (28+30+32) / 3=30 seconds; the travel time for each travel time node is the travel path length corresponding to the node divided by the preset speed of the smart car corresponding to the node.
[0033] In practice, when the production line is a door assembly line, the fixed time-consuming nodes include the door removal node, the waiting for material feeding node, the waiting for material receiving node, the waiting for warehousing node, the waiting for installation node, and the installation node; the travel time-consuming nodes include the first operating section, the material feeding section, the second operating section, the third operating section, the warehousing operating section, the warehouse adjustment operating section, the outbound operating section, the fourth operating section, and the fifth operating section; the maximum process capacity of a single intelligent vehicle is obtained by adding up the time of each node in the door assembly line.
[0034] For example, regarding the door assembly line, please refer to [link / reference]. Figure 2 , Figure 2 This is a schematic diagram of various nodes of the door assembly line shown in an exemplary embodiment of the present invention. See also: Figure 2 ① is the door disassembly node, where the disassembled door to be assembled is placed onto the intelligent trolley at the door disassembly station. ② is the waiting-for-unloading node, where the section from ① to ② is the first operating section. ③ is the unloading node, where the door to be assembled is placed onto the friction transport line for assembly. ② to ③ is the unloading section, which is moved due to the use of intelligent trolleys and friction transport. ④ is the waiting-for-receiving node, where the assembled door is placed onto an empty intelligent trolley. ③ to ④ is the friction transport section, where the intelligent trolley uses the gap under the friction transport line to pass through to ④. ⑤ The process is as follows: ④ to ⑤ is the third operation segment, where the assembled car door is stored in the door warehouse; ⑥ is the transfer point inside the door warehouse; ⑤ to ⑥ is the inbound operation segment; ⑦ is another transfer point inside the door warehouse; ⑥ to ⑦ is the transfer operation segment, where the door is moved within the door warehouse; ⑧ is the waiting installation segment; ⑦ to ⑧ is the outbound operation segment, where the assembled car door is taken out of the warehouse; ⑨ is the installation segment, where the assembled car door is installed onto the car body at the installation station; ⑧ to ⑨ is the fourth operation segment; and ⑨ to ① is the fifth operation segment, where the intelligent vehicle returns to the door removal station to pick up a new transportation task.
[0035] It should be noted that charging devices can be set up at nodes ②, ④, ⑤, ⑥, ⑦, and ⑧ to charge the smart car while it waits.
[0036] Specifically, the dismantling node, waiting for material release node, waiting for material receiving node, waiting for warehousing node, waiting for installation node, and installation node are fixed time consumption nodes; the time consumption of fixed time consumption nodes needs to be preset with fixed time consumption; the first operating section, material release section, second operating section, third operating section, warehousing operating section, warehouse transfer operating section, outbound operating section, fourth operating section, and fifth operating section are travel time consumption nodes; the time consumption of travel time consumption nodes is the travel time of the corresponding node.
[0037] It should be noted that the travel time for each travel time node is obtained by dividing the travel path length corresponding to that node by the preset speed of the smart car corresponding to that node.
[0038] Specifically, the time consumed for the door dismantling node, the waiting for material release node, the waiting for material receiving node, the waiting for warehousing node, the waiting for installation node, and the installation node are all preset fixed values.
[0039] It should be noted that the time consumed by the door disassembly node, the waiting for material release node, the waiting for material receiving node, the waiting for warehousing node, the waiting for installation node, and the installation node can be preset by default as follows on the door assembly line: 30 seconds, 60 seconds, 60 seconds, 60 seconds, 60 seconds, and 30 seconds.
[0040] Specifically, based on the first preset speed and the lengths of the first operating segment, the inbound operating segment, the transfer operating segment, the outbound operating segment, and the fourth operating segment, the travel time of the first operating segment, the inbound operating segment, the transfer operating segment, the outbound operating segment, and the fourth operating segment are obtained sequentially through the time calculation formula.
[0041] It should be noted that the first operating section, the inbound operating section, the transfer operating section, the outbound operating section, and the fourth operating section are all the same type of road sections, that is, the transportation difficulty is low. The first preset speed is used for transportation. The travel time of each section is obtained by dividing the length of each section by the first preset speed. The first preset speed is set according to specific business needs and experimental data, and the default is 30m / min.
[0042] Specifically, the travel time of the material discharge section is obtained by using a time calculation formula based on the second preset speed and the length of the material discharge section.
[0043] It should be noted that the material unloading section is the route through which the intelligent vehicle transfers the door to be assembled to the friction transport line. The transfer process is dynamic, meaning the transportation difficulty is high. Because it involves transfer actions, the second preset speed is used to traverse the length of the material unloading section. The travel time is the length of the material unloading section divided by the second preset speed. The second preset speed is set according to specific business needs and experimental data, and the default is 15m / min.
[0044] Specifically, based on the third preset speed and the lengths of the second, third, and fifth operating segments, the travel time for the second, third, and fifth operating segments is obtained sequentially using the time calculation formula.
[0045] It should be noted that the second, third, and fifth operating sections are the same type of road sections, i.e., the transportation difficulty is medium. The third preset speed is used for transportation. The travel time of each section is obtained by dividing the length of each section by the third preset speed. The third preset speed is set according to specific business needs and experimental data, and the default is 20m / min.
[0046] Specifically, the formula for calculating the time consumption is: T 耗时 = L / V; where T 耗时 For the corresponding travel time L, L is the length of the first operating section, the material feeding section, the second operating section, the third operating section, the warehousing operating section, the warehousing adjustment operating section, the warehousing operating section, the fourth operating section, or the fifth operating section; V is the first preset speed, the second preset speed, or the third preset speed corresponding to L.
[0047] It should be noted that when L is the first operating section, the inbound operating section, the warehousing operating section, the outbound operating section, or the fourth operating section, V is the first preset speed; when L is the material discharge section, V is the second preset speed; when L is the second operating section, the third operating section, or the fifth operating section, V is the third preset speed.
[0048] It is understood that the method provided in this embodiment, by refining the nodes and calculating the time consumption based on the characteristics of each node, provides effective data support for subsequent calculations.
[0049] In practice, step S12, "obtaining the stable process capability of a single intelligent vehicle based on the preset operating rate and the maximum process capability of a single intelligent vehicle," includes: obtaining the stable process capability of a single intelligent vehicle using a first formula based on the preset operating rate and the maximum process capability of a single intelligent vehicle. The first formula is: T 稳定 = T 最大 ×O 预设 Among them, T 稳定 To ensure stable process capabilities for a single intelligent vehicle, T 最大 For the maximum process capability of a single intelligent vehicle, O 预设 The preset operating rate.
[0050] It should be noted that the utilization rate, also known as equipment utilization rate, operating rate or work rate, is an indicator that measures the ratio of the actual operating time of equipment or production line to the planned available time within a specific period of time. The utilization rate is set according to specific business needs and experimental data, and the default utilization rate is 95%.
[0051] It is understood that the method provided in this embodiment, which combines a preset operating rate to obtain the stable process capability of a single intelligent vehicle, and performs scheduling based on this, can effectively improve the stability of scheduling.
[0052] In practice, step S13, "obtaining the number of intelligent vehicles on the production line based on the production line cycle time and the stable process capability of a single intelligent vehicle," includes: real-time acquisition of the production line cycle time; the cycle time is a flexible cycle time that changes constantly; and obtaining the number of intelligent vehicles on the production line based on the production line cycle time and the stable process capability of a single intelligent vehicle using the second formula; the second formula is: N = T 稳定 / T 节拍 Where N represents the number of online smart cars, and T 稳定 To ensure stable process capabilities for a single intelligent vehicle, T 节拍 This refers to the time consumed per unit, calculated based on the production line cycle time.
[0053] It should be noted that the unit of automobile production line cycle time is usually seconds per vehicle. The production line cycle time is determined by both the total customer demand and the available production time. The calculation formula is: Production line cycle time = Available production time (seconds) ÷ Total customer demand (vehicles). The time per vehicle obtained based on the production line cycle time is the time required to complete one vehicle. For example, under an 8-hour workday, if the daily demand is 100 vehicles, then the time required per vehicle is 288 seconds (8 hours × 3600 seconds = 28800 seconds; 28800 seconds / 100 vehicles = 288 seconds / vehicle). The production line cycle time per vehicle is 288 seconds.
[0054] It is understood that the method provided in this embodiment calculates the number of intelligent vehicles on the production line based on each node of the production line and the production line cycle time. When the production line cycle time changes, the number of intelligent vehicles on the production line also changes accordingly. The number of intelligent vehicles actually running on the production line is adjusted according to the number of intelligent vehicles on the production line. In this way, the number of intelligent vehicles actually running on the production line can be kept at a reasonable level, which can not only complete the transportation tasks on the production line, but also effectively avoid the waste of transportation resources caused by idle intelligent vehicles.
[0055] In practice, step S14, "determining the target number of intelligent vehicles based on the number of online intelligent vehicles", includes: obtaining the number of workstations on the production line; multiplying the number of workstations by the preset number of vehicles for each workstation to obtain the number of intelligent vehicles at the workstation; and adding the number of intelligent vehicles at the workstation, the preset redundancy number, and the number of online intelligent vehicles to obtain the target number of intelligent vehicles.
[0056] It should be noted that, considering the need to store a certain number of smart cars in the workstations and access warehouses, the preset redundancy number of smart cars in the workstations and access warehouses should be included in the calculation. The preset redundancy number is set according to specific business needs and experimental data.
[0057] It is understood that the method provided in this embodiment combines the number of redundant smart cars in the workstation and the gate warehouse to calculate the target number of smart cars, which can effectively improve the rationality of smart car scheduling.
[0058] In practice, without considering redundant design, the number of online smart cars generated can be directly used as the target number of smart cars.
[0059] It should be noted that in actual production lines, redundant designs of intelligent vehicles can be eliminated, retaining only the necessary number of intelligent vehicles, thereby effectively reducing costs and improving economic efficiency.
[0060] In practice, step S15, "scheduling intelligent vehicles according to the target number of intelligent vehicles so that the number of intelligent vehicles on the production line is the target number of intelligent vehicles," includes: when the number of intelligent vehicles actually running on the production line is lower than the target number of intelligent vehicles, scheduling n idle intelligent vehicles outside the production line to join the production line, where n = target number of intelligent vehicles - number of intelligent vehicles actually running on the production line; when the number of intelligent vehicles actually running on the production line is higher than the target number of intelligent vehicles, sorting the intelligent vehicles actually running on the production line from low to high battery level, and controlling the first n intelligent vehicles to leave the production line and go to the charging station for charging, where n = number of intelligent vehicles actually running on the production line - target number of intelligent vehicles.
[0061] It should be noted that the timing and location of the intelligent vehicles entering or leaving the production line are determined by the existing scheduling system based on the status of the intelligent vehicles on the production line, and will not be elaborated further.
[0062] In one specific embodiment, see the following for each node of the door assembly line: Figure 2 The time consumed at each node of the door assembly line is shown in Table 1 below. Table 1 As shown in Table 1, the maximum process capacity of a single intelligent vehicle is 1623 seconds; the preset operating rate is 95%; the stable process capacity of a single vehicle is 1623 × 95% = 1541.85 seconds; the cycle time of the door assembly line is 90 seconds / vehicle, meaning the time per vehicle is 90 seconds; the number of intelligent vehicles on the line is 1541.85 / 90 = 17.1316; the number of workstations is 2; the preset redundancy is 2; the target number of intelligent vehicles is 17.1316 + 2 + 2 = 21.1316. The final number of target smart cars, after rounding, is 22.
[0063] Please see Figure 3 , Figure 3This is a schematic block diagram illustrating an intelligent vehicle scheduling system for a production line according to an exemplary embodiment of the present invention. See also: Figure 3 The intelligent vehicle scheduling system 100 of this production line includes: The process capability module 101 is used to obtain the maximum process capability of a single intelligent vehicle based on multiple nodes of the production line; the maximum process capability is the time taken for a single intelligent vehicle to complete one cycle through all nodes of the production line; the stable process capability of a single intelligent vehicle is obtained based on the preset operating rate and the maximum process capability of a single intelligent vehicle. The vehicle quantity module 102 is used to obtain the number of intelligent vehicles on the production line based on the production line cycle time and the stable process capability of a single intelligent vehicle; and to determine the target number of intelligent vehicles based on the number of intelligent vehicles on the production line. The scheduling module 103 is used to schedule intelligent vehicles according to the target number of intelligent vehicles, so that the number of intelligent vehicles on the production line is the target number of intelligent vehicles.
[0064] It should be noted that the technical solution provided in this embodiment is applicable to scenarios including but not limited to: intelligent vehicle scheduling on production lines.
[0065] It should be noted that the target number of intelligent vehicles is obtained using this system. Based on the target number of intelligent vehicles and the actual number of intelligent vehicles on the production line, the existing scheduling system is used to further control the intelligent vehicles to enter or leave the production line.
[0066] It should be noted that the number of online smart cars is the minimum number of smart cars that need to be running on the production line under the current production line cycle time.
[0067] It is understood that the system provided in this embodiment obtains the maximum process capacity of a single intelligent vehicle based on multiple nodes of the production line, obtains the stable process capacity of a single intelligent vehicle based on the preset operating rate and the maximum process capacity of a single intelligent vehicle, obtains the number of intelligent vehicles on the production line based on the production line cycle time and the stable process capacity of a single intelligent vehicle, and controls the number of intelligent vehicles on the production line in real time through a scheduling system based on the number of intelligent vehicles on the production line. In this application, each node of the production line is combined with the cycle time, so that the number of intelligent vehicles on the production line can be dynamically adjusted with the flexible changes of the cycle time, so that the number of intelligent vehicles on the production line is kept at a reasonable level, which can not only complete the transportation tasks on the line, but also effectively avoid the waste of transportation resources caused by idle intelligent vehicles.
[0068] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.
[0069] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0070] It should also be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.
[0071] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.
[0072] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0073] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.
Claims
1. A method for scheduling intelligent vehicles on a production line, characterized in that, The method includes: The maximum process capacity of a single intelligent vehicle is obtained based on multiple nodes of the production line; the maximum process capacity is the time taken for a single intelligent vehicle to complete one cycle through all nodes of the production line. The stable process capability of a single intelligent vehicle is obtained based on the preset operating rate and the maximum process capability of a single intelligent vehicle. The number of intelligent vehicles on the production line is determined based on the production line cycle time and the stable process capability of a single intelligent vehicle. The target number of intelligent vehicles is determined based on the number of online intelligent vehicles. The intelligent vehicles are scheduled according to the target number of intelligent vehicles, so that the number of intelligent vehicles on the production line is the target number of intelligent vehicles.
2. The method according to claim 1, characterized in that, The process of obtaining the stable process capability of a single intelligent vehicle based on the preset operating rate and the maximum process capability of a single intelligent vehicle includes: Based on the preset operating rate and the maximum process capacity of a single intelligent vehicle, the stable process capacity of a single intelligent vehicle is obtained through the first formula, which is: T 稳定 = T 最大 ×O 预设 ; Among them, T 稳定 To ensure stable process capabilities for a single intelligent vehicle, T 最大 For the maximum process capability of a single intelligent vehicle, O 预设 The preset operating rate.
3. The method according to claim 2, characterized in that, The determination of the number of intelligent vehicles on the production line based on the production line cycle time and the stable process capability of a single intelligent vehicle includes: Real-time acquisition of the production line cycle time; The number of intelligent vehicles on the production line is obtained using a second formula based on the production line cycle time and the stable process capability of a single intelligent vehicle; the second formula is: N = T 稳定 / T 节拍 ; Where N represents the number of online smart cars, T 稳定 To ensure stable process capabilities for a single intelligent vehicle, T 节拍 This refers to the time consumed per unit, calculated based on the production line cycle time.
4. The method according to claim 1, characterized in that, The method of obtaining the maximum process capability of a single intelligent vehicle based on multiple nodes of the production line includes: The production line includes multiple nodes with fixed time consumption and nodes with travel time consumption; the time consumption of the fixed time consumption node is a preset fixed time consumption, and the time consumption of the travel time consumption node is the travel time consumption. The maximum process capacity of a single intelligent vehicle is obtained by adding the time consumed at each fixed time-consuming node in the production line to the time consumed at each driving time-consuming node.
5. The method according to claim 4, characterized in that, The step of adding the time consumed at each fixed time-consuming node in the production line to the time consumed at each travel time-consuming node to obtain the maximum process capacity of the single intelligent vehicle includes: When the production line is a door assembly line, the fixed time-consuming nodes include the door disassembly node, the waiting-to-feed node, the waiting-to-receive node, the waiting-to-warehouse node, the waiting-to-install node, and the installation node; the travel time-consuming nodes include the first operating section, the feeding section, the second operating section, the third operating section, the warehousing operating section, the warehouse adjustment operating section, the outbound operating section, the fourth operating section, and the fifth operating section. The maximum process capacity of a single intelligent vehicle is obtained by adding up the time consumed at each node in the door assembly line.
6. The method according to claim 5, characterized in that, The time consumed by the door dismantling node, the waiting for material release node, the waiting for material receiving node, the waiting for warehousing node, the waiting for installation node, and the installation node are all preset fixed values.
7. The method according to claim 5, characterized in that, The method further includes: Based on the first preset speed and the lengths of the first operating segment, the inbound operating segment, the transfer operating segment, the outbound operating segment, and the fourth operating segment, the travel time of the first operating segment, the inbound operating segment, the transfer operating segment, the outbound operating segment, and the fourth operating segment are obtained in sequence through the time calculation formula. The travel time of the material discharge section is obtained by using the time calculation formula based on the second preset speed and the length of the material discharge section. Based on the third preset speed and the lengths of the second, third, and fifth operating segments, the travel time for the second, third, and fifth operating segments is obtained sequentially using the time calculation formula.
8. The method according to claim 7, characterized in that, The formula for calculating the time consumption is: T 耗时 = L / V ; Among them, T 耗时 For the corresponding travel time L, L is the length of the first operating section, the material feeding section, the second operating section, the third operating section, the warehousing operating section, the warehousing adjustment operating section, the warehousing operating section, the fourth operating section, or the fifth operating section; V is the first preset speed, the second preset speed, or the third preset speed corresponding to L.
9. The method according to claim 1, characterized in that, Determining the target number of smart cars based on the number of online smart cars includes: Obtain the number of workstations on the production line; Multiply the number of workstations by the preset number of carts per workstation to obtain the number of intelligent carts at each workstation. The target number of intelligent vehicles is obtained by adding the number of intelligent vehicles at the workstation, the preset redundancy number, and the number of intelligent vehicles on the line.
10. The method according to claim 1, characterized in that, The step of scheduling intelligent vehicles according to the target number of intelligent vehicles, so that the number of intelligent vehicles on the production line is the target number of intelligent vehicles, includes: When the number of intelligent vehicles actually running on the production line is less than the target number of intelligent vehicles, n idle intelligent vehicles outside the production line are scheduled to be incorporated into the production line, where n = target number of intelligent vehicles - number of intelligent vehicles actually running on the production line. When the number of smart cars actually running on the production line is higher than the target number of smart cars, the smart cars actually running on the production line are sorted from low to high battery level, and the first n smart cars are controlled to leave the production line and go to the charging station for charging, where n = the number of smart cars actually running on the production line - the target number of smart cars.
11. An intelligent vehicle scheduling system for a production line, characterized in that, The system includes: The process capability module is used to obtain the maximum process capability of a single intelligent vehicle based on multiple nodes of the production line; the maximum process capability is the time taken for a single intelligent vehicle to complete one cycle through all nodes of the production line; and the stable process capability of a single intelligent vehicle is obtained based on the preset operating rate and the maximum process capability of the single intelligent vehicle. The vehicle quantity module is used to obtain the number of intelligent vehicles on the production line based on the production line cycle time and the stable process capability of a single intelligent vehicle; and to determine the target number of intelligent vehicles based on the number of intelligent vehicles on the production line. The scheduling module is used to schedule intelligent vehicles according to the target number of intelligent vehicles, so that the number of intelligent vehicles on the production line is the target number of intelligent vehicles.