WO2023193236A1 - Agv系统以及agv调度方法 - Google Patents

Agv系统以及agv调度方法 Download PDF

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WO2023193236A1
WO2023193236A1 PCT/CN2022/085811 CN2022085811W WO2023193236A1 WO 2023193236 A1 WO2023193236 A1 WO 2023193236A1 CN 2022085811 W CN2022085811 W CN 2022085811W WO 2023193236 A1 WO2023193236 A1 WO 2023193236A1
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agv
threshold
value
scheduling
production equipment
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PCT/CN2022/085811
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French (fr)
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林立勇
史德强
陈书睿
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宁德时代新能源科技股份有限公司
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Priority to CN202280031295.1A priority Critical patent/CN117223020A/zh
Priority to PCT/CN2022/085811 priority patent/WO2023193236A1/zh
Publication of WO2023193236A1 publication Critical patent/WO2023193236A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"

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  • This application relates to the field of AGV (Automated Guided Vehicle), and in particular to an AGV scheduling method and AGV system.
  • AGV Automated Guided Vehicle
  • This application is aimed at improving the existing AGV system.
  • this application provides an AGV system and an AGV scheduling method that can optimize the scheduling of each AGV in the AGV system and prevent peaks and troughs in AGV transportation demand and/or AGV charging demand. Wave peaks and troughs, thereby improving AGV utilization and production line productivity.
  • an AGV scheduling method including: obtaining the optimal value of the threshold value of the AGV scheduling-related parameters, including: using a pre-established simulation model for the actual AGV system, targeting the AGV scheduling-related parameters Simulate different values of the threshold to determine the obtained values of the relevant performance indicators under the corresponding values of the threshold; and obtain the threshold values of the AGV scheduling parameters corresponding to the obtained values of the relevant performance indicators that meet the preset conditions.
  • the value is used as the optimal value of the threshold value of AGV scheduling related parameters; and the optimal value of the threshold value of AGV scheduling related parameters is used for AGV scheduling in the actual AGV system.
  • the scheduling parameter threshold values corresponding to the optimal values of the different performance indicators considered for the AGV system can be simulated (for example, in the planning stage), so that all AGV systems can be used in the actual AGV system.
  • the obtained scheduling parameter threshold value can be used to achieve the optimal performance index of the AGV system.
  • the thresholds of parameters related to AGV scheduling include one or both of a first threshold corresponding to the remaining material processing time of the production equipment and a second threshold corresponding to the remaining power of the AGV, and wherein the relevant performance Indicators include one or both of AGV utilization and production line productivity.
  • This embodiment is a preferred example of thresholds and related performance indicators for AGV scheduling related parameters.
  • AGV utilization and production line productivity are the preferred goals. Optimization of the first threshold corresponding to the remaining material processing time of the production equipment can globally coordinate and optimize the generation and scheduling of AGV transportation tasks, thereby preventing the generation and scheduling of AGV transport tasks.
  • the peaks and troughs of transportation demand; and the optimization of the second threshold corresponding to the remaining power of AGV can optimize the generation of AGV charging tasks, stagger the AGV charging time period, prevent the generation of peaks and troughs of AGV charging demand, and reduce AGV charging congestion. and waiting for charging.
  • an AGV transportation task is generated to schedule the AGV to supply materials to the production equipment, and when the remaining power of the AGV is lower than the second threshold
  • an AGV charging task is generated to schedule the AGV to charge at the charging pile.
  • the simulation is performed to determine the resulting values of the relevant performance indicators based on at least one of the following factors: number of work orders, number of AGVs, number of production equipment, material handling rate of the production equipment, AGV capacity, AGV movement Speed, initial power of AGV, ratio of number of AGVs to number of AGV charging piles, AGV charging rate.
  • This limitation on the parameters used in the process of finding the optimal threshold value gives various factors that affect the threshold value, so that the found threshold value can better reflect the situation of the real AGV system. And be able to achieve the required optimal performance indicators of the real system (such as AGV utilization and/or production line productivity).
  • the greater the number of work orders, the smaller the number of AGVs, the lower the production rate of the production equipment, the higher the AGV transport capacity, and the faster the AGV moving speed the smaller the optimal value of the first threshold is.
  • the optimal value of the threshold can be found more quickly, and the found value can be The optimal value obtained can better reflect the conditions of the real AGV system and achieve the required optimal performance indicators of the real system (such as AGV utilization and/or production line productivity).
  • the optimal value of the threshold can be found more quickly, and the found value can be The optimal value obtained can better reflect the conditions of the real AGV system and achieve the required optimal performance indicators of the real system (such as AGV utilization and/or production line productivity).
  • the simulation determines corresponding line yields for values in a first range corresponding to the first threshold and/or values in a second range corresponding to the second threshold.
  • the threshold value can be simulated within a desired range, thereby shortening the simulation time and finding the desired threshold value more efficiently.
  • the lower limit of the first range is calculated based on the transportation capacity of the AGV and the material processing rate of the production equipment
  • the upper limit of the first range is calculated based on the transportation capacity of the AGV, the material processing rate of the production equipment, and the material processing rate of the production equipment. Material storage capacity is calculated.
  • the lower limit of the second range is calculated based on the current position of the AGV, the moving speed of the AGV, and the position of the charging pile.
  • the range of the threshold value that needs to be simulated can be narrowed to a greater extent, thereby shortening the simulation time to a greater extent and finding the target more efficiently. Output the desired threshold value.
  • the obtained value of the relevant performance index that meets the preset conditions is the highest value of AGV utilization and/or the highest value of production line productivity.
  • preferred examples of performance indicators are given, that is, the highest values of AGV utilization and production line productivity. This enables maximum utilization of AGV systems and production equipment, thereby reducing production costs and improving effectiveness.
  • the determined first threshold corresponding to the highest AGV utilization and/or the highest production line productivity is different for at least a part of the production equipment; and/or for at least one of the AGVs
  • the determined second threshold corresponding to the highest AGV utilization and/or the highest production line productivity is different.
  • the initial conditions of each AGV and/or production equipment such as power, operating time, wear, etc.
  • the final threshold value for each AGV and/or production equipment can fully reflect the situation in the actual system, so that the optimal production line productivity and/or AGV utilization can be achieved for the actual system.
  • the simulation is performed with the aid of Plant Simulation or Flexsim simulation software.
  • the method of the present application can be executed more conveniently and quickly.
  • an AGV system including: an AGV; an AGV simulation system.
  • the AGV simulation system is configured to obtain optimal values of thresholds for parameters related to AGV scheduling, including: through pre-established parameters for actual
  • the simulation model of the AGV system simulates different values of the thresholds of parameters related to AGV scheduling to determine the values of the relevant performance indicators under the corresponding values of the thresholds; and obtain the values of the relevant performance indicators that meet the preset conditions.
  • the value of the corresponding threshold value of the AGV scheduling related parameter is used as the optimal value of the threshold value of the AGV scheduling related parameter; and the AGV scheduling controller, the AGV scheduling controller is configured to apply the optimal value of the threshold value of the AGV scheduling related parameter to schedule AGV.
  • the scheduling parameter threshold values corresponding to the optimal values of the different performance indicators considered in the AGV system can be simulated (for example, in the planning stage), so that the obtained values can be used in the actual AGV system.
  • the scheduling parameter threshold value can be selected to achieve the optimal performance index of the AGV system.
  • the thresholds of parameters related to AGV scheduling include one or both of a first threshold corresponding to the remaining material processing time of the production equipment and a second threshold corresponding to the remaining power of the AGV, and wherein the relevant performance Indicators include one or both of AGV utilization and production line productivity.
  • This embodiment is a preferred example of thresholds and related performance indicators for AGV scheduling related parameters.
  • AGV utilization and production line productivity are the preferred goals. Optimization of the first threshold corresponding to the remaining material processing time of the production equipment can globally coordinate and optimize the generation and scheduling of AGV transportation tasks, thereby preventing the generation and scheduling of AGV transport tasks.
  • the peaks and troughs of transportation demand; and the optimization of the second threshold corresponding to the remaining power of AGV can optimize the generation of AGV charging tasks, stagger the AGV charging time period, prevent the generation of peaks and troughs of AGV charging demand, and reduce AGV charging congestion. and waiting for charging.
  • an AGV transportation task is generated to schedule the AGV to supply materials to the production equipment, and when the remaining power of the AGV is lower than the second threshold
  • an AGV charging task is generated to schedule the AGV to charge at the charging pile.
  • the obtained value of the relevant performance index that meets the preset conditions is the highest value of AGV utilization and/or the highest value of production line productivity.
  • preferred examples of performance indicators are given, that is, the highest values of AGV utilization and production line productivity. This enables maximum utilization of AGV systems and production equipment, thereby reducing production costs and improving effectiveness.
  • the determined value of the first threshold corresponding to the highest AGV utilization and/or the highest production line productivity is different for at least a part of the production equipment; and/or for the AGV For at least part of them, the determined value of the second threshold corresponding to the highest AGV utilization rate and/or the highest production line productivity is different.
  • the initial conditions of each AGV and/or production equipment such as power, operating time, wear, etc.
  • the final threshold value for each AGV and/or production equipment can fully reflect the situation in the actual system, so that the optimal production line productivity and/or AGV utilization can be achieved for the actual system. .
  • Figure 1 is an example flow chart of an AGV scheduling method according to an embodiment of the present application
  • Figure 2 is an example flow chart of a method for obtaining an optimal threshold value according to an embodiment of the present application.
  • FIG. 3 is a schematic block diagram of an AGV system according to an embodiment of the present application.
  • an embodiment means that a particular feature, structure or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application.
  • the appearances of this phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those skilled in the art understand, both explicitly and implicitly, that the embodiments described herein may be combined with other embodiments.
  • the AGV system can replace manual handling and precise and flexible distribution.
  • the dispatch controller included in the AGV system is responsible for AGV transportation task allocation, path planning and scheduling, and/or charging management and other functions.
  • thresholds associated with multiple AGV scheduling-related parameters need to be used as trigger conditions to trigger corresponding work tasks.
  • the AGV scheduling system will generate AGV transportation tasks based on the remaining material processing time of the production equipment, assign the generated AGV transportation tasks to different AGVs, and perform corresponding path planning and scheduling for the AGVs to transport the production equipment. Generate materials; when the AGV power is lower than some established thresholds, the AGV dispatch control system will generate an AGV charging task and assign the AGV to the corresponding charging pile for charging; and so on.
  • the existing AGV dispatching control system uses artificially prescribed fixed thresholds for these thresholds. It neither considers the needs of actual production conditions nor performs corresponding threshold optimization design, thus failing to optimize and improve various aspects of the AGV system. Relevant performance indicators (such as AGV utilization and production line productivity (i.e., the productivity of production equipment)). For example, this artificially prescribed fixed threshold may cause equipment to stop waiting for materials, thereby reducing production line productivity; or it may cause AGV charging congestion and waiting for charging, reducing AGV utilization; and so on.
  • AGV utilization and production line productivity i.e., the productivity of production equipment
  • this application in order to optimize the required performance indicators of the AGV system (such as AGV utilization and production line productivity), this application provides an AGV system and an AGV scheduling method that can optimize the scheduling of each AGV in the AGV system, thereby Obtain optimal required performance metrics.
  • the following embodiment takes the generation of sealing nail welding defect samples for power batteries as an example.
  • FIG. 1 is an example flow chart of an AGV scheduling method 100 according to an embodiment of the present application.
  • the method 100 starts with step 110, where the optimal value of the threshold value of the AGV scheduling-related parameters is obtained.
  • the optimal value of the threshold can optimize the relevant performance indicators of the AGV system.
  • the relevant performance indicators may include one or both of AGV utilization and production line productivity. Therefore, the optimal value of the threshold value of parameters related to AGV scheduling will optimize AGV utilization and/or production line productivity.
  • the thresholds of parameters related to AGV scheduling may include one or both of a first threshold corresponding to the remaining material processing time of the production equipment and a second threshold corresponding to the remaining power of the AGV.
  • the optimal value of the first threshold corresponding to the remaining material processing time of the production equipment will be able to globally coordinate and optimize the generation and scheduling of AGV transportation tasks, thereby preventing peaks and peaks in AGV transportation demand.
  • the optimal value of the second threshold corresponding to the remaining power of the AGV can optimize the generation of AGV charging tasks, stagger the AGV charging time period, prevent the peaks and valleys of AGV charging demand, and reduce AGV charging congestion and charging waiting. .
  • the first threshold is used to generate and schedule AGV transportation tasks, that is, when the remaining material processing time of the production equipment is lower than the first threshold, an AGV transportation task is generated to schedule the AGV to supply materials to the production equipment.
  • the second threshold is used to generate and schedule AGV charging tasks, that is, when the remaining power of the AGV is lower than the second threshold, an AGV charging task is generated to schedule the AGV to charge at the charging pile.
  • thresholds are only examples of parameter thresholds used in AGV systems, and there may also be various other suitable parameter thresholds (such as the backlog of products produced by production equipment on the production line) and They can all be optimized and applied according to the method and system of this application, and will not be described again here.
  • AGV transportation tasks and AGV charging tasks can be automatically and intelligently generated in the AGV system, thereby better preventing peaks and troughs in AGV transportation demand and peaks in AGV charging demand. and trough, thus improving AGV utilization and production line productivity.
  • obtaining the optimal value of the threshold value of the AGV scheduling-related parameter can be performed in any suitable manner.
  • Figure 2 shows an example of the acquisition method.
  • step 102 a pre-established simulation model for the actual AGV system is used to simulate different values of the thresholds of AGV scheduling related parameters to determine the relevant performance under the corresponding values of the thresholds.
  • the resulting value of the indicator is shown.
  • the simulation is performed with the aid of Plant Simulation or Flexsim simulation software.
  • the method of the present application can be executed more conveniently and quickly.
  • the simulation software Plant Simulation to build a simulation model of the AGV system (and any required upper/lower systems) (including at least AGV task generation, AGV task allocation, AGV path planning and scheduling, charging management and other modules), and Define thresholds that need to be optimized (such as the threshold corresponding to the remaining material processing time of the production equipment and the threshold corresponding to the remaining power of the AGV) and performance indicators (such as AGV utilization and/or production line productivity) that need to be optimized in the simulation model, Then, for each set of threshold values, ensure that modules such as AGV task allocation, path planning and scheduling remain unchanged, and the performance indicators are calculated through Plant Simulation simulation. Then the optimal performance index can be determined based on the calculated performance index, and a set of threshold values corresponding to the optimal performance index can be obtained.
  • the thresholds of parameters related to AGV scheduling may include one or both of a first threshold corresponding to the remaining material processing time of the production equipment and a second threshold corresponding to the remaining power of the AGV.
  • the simulation may be performed to determine the resulting values of the relevant performance indicators based on at least one of the following factors: number of work orders, number of AGVs, number of production equipment, material handling rate of the production equipment, AGV transport capacity, AGV Moving speed, AGV initial power, ratio of the number of AGVs to the number of AGV charging piles, AGV charging rate, etc.
  • the limitation of the parameters used in the process of finding the optimal threshold value gives various factors that affect the threshold value, so that the found threshold value can better reflect The conditions of the real AGV system and being able to achieve the required optimal performance indicators of the real system (such as AGV utilization and/or production line productivity).
  • the optimal value of the threshold can be found more quickly, and the found value can be The optimal value obtained can better reflect the conditions of the real AGV system and achieve the required optimal performance indicators of the real system (such as AGV utilization and/or production line productivity).
  • the greater the number of work orders the greater the ratio of the number of AGVs to the number of AGV charging piles, the faster the AGV charging rate, and the faster the AGV moving speed, the smaller the optimal value of the second threshold will be.
  • the optimal value of the threshold can be found more quickly, and the found value can be The optimal value obtained can better reflect the conditions of the real AGV system and achieve the required optimal performance indicators of the real system (such as AGV utilization and/or production line productivity).
  • the thresholds of parameters related to AGV scheduling may include one or both of a first threshold corresponding to the remaining material processing time of the production equipment and a second threshold corresponding to the remaining power of the AGV, in order to shorten the simulation Time, the simulation may determine corresponding line yields for values in a first range corresponding to the first threshold and/or values in a second range corresponding to the second threshold.
  • the threshold value can be simulated within a desired range, thereby shortening the simulation time and finding the desired threshold value more efficiently.
  • the lower limit of the first range is calculated based on the transportation capacity of the AGV and the material processing rate of the production equipment
  • the upper limit of the first range is calculated based on the transportation capacity of the AGV, the material processing rate of the production equipment, and the production equipment. Material storage capacity is calculated.
  • the value range of the first threshold by further limiting the value range of the first threshold, the range of the threshold value that needs to be simulated can be narrowed to a greater extent, thereby shortening the simulation time to a greater extent and finding the value more efficiently.
  • the lower limit of the second range is calculated based on the current position of the AGV, the moving speed of the AGV, and the position of the charging pile.
  • the range of the threshold value that needs to be simulated can be narrowed to a greater extent, thereby shortening the simulation time to a greater extent and finding the target more efficiently. Output the desired threshold value.
  • the obtained value of the relevant performance index that meets the preset conditions is the highest value of AGV utilization and/or the highest value of production line productivity.
  • preferred examples of performance indicators are given, that is, the highest values of AGV utilization and production line productivity. This enables maximum utilization of AGV systems and production equipment, thereby reducing production costs and improving effectiveness.
  • the determined first threshold corresponding to the highest AGV utilization and/or the highest production line yield is different for at least a part of the production equipment; and/or for at least one of the AGVs At least in part, the determined second threshold corresponding to the highest AGV utilization and/or the highest production line productivity is different.
  • each AGV and/or production equipment is fully considered by setting different threshold values for each AGV and/or production equipment.
  • the initial conditions of the production equipment (such as power, working time, wear, etc.) are different, so that the final threshold value for each AGV and/or production equipment can fully reflect the situation in the actual system, so that it can Achieve optimal line productivity and/or AGV utilization for this actual system.
  • the method 200 may include taking the value of the threshold value of the AGV scheduling-related parameter corresponding to the obtained value of the relevant performance index that meets the preset conditions as the optimal value of the threshold value of the AGV scheduling-related parameter. .
  • the method 100 may include applying optimal values of thresholds of parameters related to AGV scheduling to perform AGV scheduling in the actual AGV system. Therefore, through this AGV scheduling method 100, the scheduling parameter threshold values corresponding to the optimal values of the different performance indicators considered of the AGV system can be simulated (for example, in the planning stage), so that the actual AGV can The obtained scheduling parameter threshold value is used in the system to achieve the optimal performance index of the AGV system.
  • FIG. 3 is a schematic block diagram of an AGV system 300 according to one embodiment of the present application.
  • the AGV system 300 may include an AGV scheduling controller 310, an AGV 320, and an AGV simulation system 330. It will be appreciated that the AGV scheduling controller 310, the AGV 320, and the AGV simulation system 330 may be capable of communicating with each other, as shown in the lightning shape shown in Figure 3. Of course, this communication can take any other suitable form, such as the AGV 310 and the AGV simulation system 330 may not be directly imaged, but may communicate via the AGV scheduling controller 310 as an intermediary, and so on.
  • the AGV system 300 may include any number of AGVs, as shown by ellipsis 340 in FIG. 3 .
  • the AGV scheduling controller 310 is shown in the form of a server in FIG. 3, those skilled in the art will understand that this is only an example and the AGV scheduling controller 310 may take any suitable form, such as on the cloud.
  • the AGV simulation system 330 may be configured to obtain optimal values of thresholds for parameters related to AGV scheduling. Further according to this embodiment, this may include conducting simulations for different values of the thresholds of parameters related to AGV scheduling through a pre-established simulation model for the actual AGV system 300 to determine the results of relevant performance indicators under corresponding values of the thresholds. value; and take the value of the threshold value of the AGV scheduling-related parameter corresponding to the value obtained by the relevant performance index that meets the preset conditions as the optimal value of the threshold value of the AGV scheduling-related parameter. Subsequently, the AGV scheduling controller 310 may be configured to receive and apply the optimal value from the AGV simulation system 330 to schedule the AGV 320.
  • the scheduling parameter threshold values corresponding to the optimal values of the different performance indicators considered in the AGV system can be simulated (for example, in the planning stage), so that all the scheduling parameters can be used in the actual AGV system.
  • the obtained scheduling parameter threshold value can be used to achieve the optimal performance index of the AGV system.
  • the thresholds of parameters related to AGV scheduling may include one or both of a first threshold corresponding to the remaining material processing time of the production equipment and a second threshold corresponding to the remaining power of the AGV, and wherein Relevant performance indicators include one or both of AGV utilization and production line productivity.
  • This embodiment is a preferred example of thresholds and related performance indicators for AGV scheduling related parameters.
  • AGV utilization and production line productivity are the preferred goals. Optimization of the first threshold corresponding to the remaining material processing time of the production equipment can globally coordinate and optimize the generation and scheduling of AGV transportation tasks, thereby preventing the generation and scheduling of AGV transport tasks.
  • the peaks and troughs of transportation demand; and the optimization of the second threshold corresponding to the remaining power of AGV can optimize the generation of AGV charging tasks, stagger the AGV charging time period, prevent the generation of peaks and troughs of AGV charging demand, and reduce AGV charging congestion. and waiting for charging.
  • an AGV transportation task is generated to schedule the AGV to supply materials to the production equipment, and when the remaining power of the AGV is lower than the second threshold
  • an AGV charging task is generated to schedule the AGV to charge at the charging pile.
  • the obtained value of the relevant performance index that meets the preset conditions is the highest value of AGV utilization and/or the highest value of production line productivity.
  • preferred examples of performance indicators are given, that is, the highest values of AGV utilization and production line productivity. This enables maximum utilization of AGV systems and production equipment, thereby reducing production costs and improving effectiveness.
  • the determined first threshold corresponding to the highest AGV utilization and/or the highest production line yield is different for at least a part of the production equipment; and/or for at least one of the AGVs At least in part, the determined second threshold corresponding to the highest AGV utilization and/or the highest production line productivity is different.
  • each AGV and/or production equipment is fully considered by setting different threshold values for each AGV and/or production equipment.
  • the initial conditions of the production equipment (such as power, working time, wear, etc.) are different, so that the final threshold value for each AGV and/or production equipment can fully reflect the situation in the actual system, so that it can Achieve optimal line productivity and/or AGV utilization for this actual system.
  • AGV dispatch controller 310 and the AGV simulation system 330 are shown as separate components in Figure 3, those skilled in the art will understand that they may be located in one place or they may each be split into multiple subsystems (as long as these subsystems can to achieve the above functions).
  • the technical solution of this application can optimize the threshold related to the remaining material processing time of the production equipment.
  • the relevant AGV scheduling controller of the AGV system will automatically assign the AGV transportation task to one or more selected AGVs in the AGV system for material transportation.
  • the technical solution of this application can also optimize the threshold related to the remaining power of the AGV.
  • the relevant AGV dispatch controller of the AGV system will automatically generate a charging task for the AGV and assign the AGV to the corresponding charging pile for charging.
  • the technical solution of this application can optimize the thresholds related to the remaining material processing time of the production equipment and the remaining power of the AGV in the planning stage through AGV system simulation and calling the optimization algorithm library, so as to automatically and intelligently generate and schedule AGV transportation tasks and AGV charging tasks, so as to globally coordinate and optimize AGV utilization and improve production line productivity.

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Abstract

本申请涉及一种AGV系统以及AGV调度方法，其能够优化AGV系统中的各AGV的调度，防止产生对AGV运输需求的波峰和波谷和/或AGV充电需求的波峰和波谷，从而提高AGV利用率和产线产率。该AGV调度方法可包括：获取AGV调度有关参数的阈值的最优取值，包括：通过预先建立的针对实际AGV系统的仿真模型，针对AGV调度有关参数的阈值的不同取值进行仿真，以确定在阈值的相应取值下相关性能指标的所得值；以及取与相关性能指标的符合预设条件的所得值相对应的AGV调度有关参数的阈值的取值作为AGV调度有关参数的阈值的最优取值；以及在实际AGV系统中应用AGV调度有关参数的阈值的最优取值来进行AGV调度。

Description

AGV系统以及AGV调度方法 技术领域
本申请涉及AGV(Automated Guided Vehicle，自动导引运输车)领域，特别是涉及一种AGV调度方法以及AGV系统。
背景技术
当今，智能物流在社会活动中的作用越来越大，尤其是对于无人化和智能化工厂而言。作为物流系统的一个重要组成部分，AGV系统有着可以替代人工搬运和精准柔性配送的作用。
然而，现有的AGV系统以及相关的AGV调度方法仍然存在许多需要改进的方面。例如，在现有的AGV系统中，只有简单地设定的触发阈值，用于触发各种AGV任务(诸如AGV运输任务、AGV充电任务等等)的生成。这种简单的阈值设定不利地影响了AGV系统的效率，没有有效地优化和提升AGV利用率、产线产能等等。
本申请正是针对现有AGV系统作出的改进。
发明内容
鉴于现有AGV系统中的问题，本申请提供了一种AGV系统以及AGV调度方法，能够优化AGV系统中的各AGV的调度，防止产生对AGV运输需求的波峰和波谷和/或AGV充电需求的波峰和波谷，从而提高AGV利用率和产线产率。
根据本申请的第一方面，提供了一种AGV调度方法，包括：获取AGV调度有关参数的阈值的最优取值，包括：通过预先建立的针对实际AGV系统的仿真模型，针对AGV调度有关参数的阈值的不同取值进行仿真，以确定在阈值的相应取值下相关性能指标的所得值；以及取与相关性能指标的符合预设条件的所得值相对应的AGV调度有关参数的阈值的取 值作为AGV调度有关参数的阈值的最优取值；以及在实际AGV系统中应用AGV调度有关参数的阈值的最优取值来进行AGV调度。
通过这一AGV调度方法，可以(例如在规划阶段)仿真出与AGV系统的所考虑的不同性能指标的最优值相对应的调度参数阈值取值，由此可以在实际的AGV系统中使用所得到的调度参数阈值取值，从而能够达到AGV系统的最优性能指标。
根据一实施例，AGV调度有关参数的阈值包括与生产设备的剩余物料处理时间相对应的第一阈值以及与AGV的剩余电量相对应的第二阈值中的一者或两者，并且其中相关性能指标包括AGV利用率以及产线产率中的一者或两者。该实施例是AGV调度有关参数的阈值和相关性能指标的优选示例。AGV利用率以及产线产率是优选的目标，其中针对与生产设备的剩余物料处理时间相对应的第一阈值的优化能够从全局协同和优化AGV运输任务的生成及调度，从而防止产生对AGV运输需求的波峰和波谷；而针对与AGV的剩余电量相对应的第二阈值的优化能够优化AGV充电任务的生成，错开AGV充电时间段，防止产生AGV充电需求的波峰和波谷，减少AGV充电拥堵和充电等待。
根据另一实施例，在生产设备的剩余物料处理时间低于第一阈值的情况下，生成AGV运输任务以调度AGV向该生产设备供应物料，并且在AGV的剩余电量低于第二阈值的情况下，生成AGV充电任务以调度该AGV去往充电桩进行充电。通过上述第一阈值和第二阈值，能够在AGV系统中自动地且智能地生成AGV运输任务和AGV充电任务，从而能够更好地防止产生对AGV运输需求的波峰和波谷以及AGV充电需求的波峰和波谷。
根据又一实施例，仿真根据以下各个因素中的至少一者来进行以确定相关性能指标的所得值：工单数量、AGV数量、生产设备数量、生产设备的物料处理速率、AGV运力、AGV移动速度、AGV初始电量、AGV数量与AGV充电桩数目的比值、AGV充电速率。对最优阈值取值的找出过程中所使用的参数的这一限定给出了对阈值取值有影响的各个因素，从而使得所找出的阈值取值更能够反映真实AGV系统的状况，并能够达到 真实系统的所需最优性能指标(诸如AGV利用率和/或产线产率)。
根据又一实施例，工单数量越多、AGV数量越少、生产设备的生产速率越低、AGV的运力越高、AGV的移动速度越快，则第一阈值的最优取值越小。在该实施例中，通过对影响第一阈值的优选参数进行选择，并进一步给出这些优选参数对第一阈值的具体影响，能够更快地找出阈值的最优取值，且使得所找出的最优取值更能够反映真实AGV系统的状况，并能够达到真实系统的所需最优性能指标(诸如AGV利用率和/或产线产率)。
根据又一实施例，工单数量越多、AGV数量与AGV充电桩数目的比值越大、AGV的充电速率越快、AGV的移动速度越快，则第二阈值的最优取值越小。在该实施例中，通过对影响第二阈值的优选参数进行选择，并进一步给出这些优选参数对第二阈值的具体影响，能够更快地找出阈值的最优取值，且使得所找出的最优取值更能够反映真实AGV系统的状况，并能够达到真实系统的所需最优性能指标(诸如AGV利用率和/或产线产率)。
根据又一实施例，仿真针对与第一阈值相对应的第一范围中的值和/或与第二阈值相对应的第二范围中的值来确定相应的产线产率。在该实施例中，通过对仿真过程中的阈值取值范围的限定，使得能够在合需的范围内对阈值进行仿真，从而缩短仿真时间，更高效地找出合需的阈值取值。
根据又一实施例，第一范围的下限是基于AGV的运力和生产设备的物料处理速率来计算得到的，并且第一范围的上限是基于AGV的运力、生产设备的物料处理速率以及生产设备的物料存储容量来计算得到的。在该实施例中，通过对第一阈值的取值范围的进一步限定，使得能够在更大的程度上缩小需要仿真的阈值取值范围，从而在更大程度上缩短仿真时间，更高效地找出合需的阈值取值。
根据又一实施例，第二范围的下限是基于AGV的当前位置、AGV的移动速度以及充电桩的位置来计算得到的。在该实施例中，通过对第二阈值的取值范围的进一步限定，使得能够在更大的程度上缩小需要仿真的阈值取值范围，从而在更大程度上缩短仿真时间，更高效地找出合需的阈 值取值。
根据又一实施例，相关性能指标的符合预设条件的所得值是与AGV利用率的最高值和/或产线产率的最高值。在该实施例中，给出了性能指标的优选示例，即AGV利用率以及产线产率的最高值。这使得能够在最大程度上利用AGV系统和生产设备，从而降低生产成本，提高成效。
根据又一实施例，对于生产设备中的至少一部分而言，所确定的与最高AGV利用率和/或最高产线产率相对应的第一阈值是不同的；和/或对于AGV中的至少一部分而言，所确定的与最高AGV利用率和/或最高产线产率相对应的第二阈值是不同的。在该实施例中，通过针对每一AGV和/或生产设备设定不同的阈值取值，充分考虑了各个AGV和/或生产设备的初始条件(诸如电量、已工作时间、磨损等等)的不同，因此使得最终获得的针对每一AGV和/或生产设备的阈值取值能够充分反映实际系统中的情形，从而能够针对该实际系统达到其最优的产线产率和/或AGV利用率。
根据又一实施例，仿真是借助于Plant Simulation或Flexsim仿真软件来执行的。在该实施例中，通过使用普通的仿真软件，能够更方便且快捷地执行本申请的方法。
根据本公开的第二方面，提供了一种AGV系统，包括：AGV；AGV仿真系统，AGV仿真系统被配置成获取AGV调度有关参数的阈值的最优取值，包括：通过预先建立的针对实际AGV系统的仿真模型，针对AGV调度有关参数的阈值的不同取值进行仿真，以确定在阈值的相应取值下相关性能指标的所得值；以及取与相关性能指标的符合预设条件的所得值相对应的AGV调度有关参数的阈值的取值作为AGV调度有关参数的阈值的最优取值；以及AGV调度控制器，AGV调度控制器被配置成应用AGV调度有关参数的阈值的最优取值来调度AGV。
通过这一AGV系统，可以(例如在规划阶段)仿真出与AGV系统的所考虑的不同性能指标的最优值相对应的调度参数阈值取值，由此可以在实际的AGV系统中使用所得到的调度参数阈值取值，从而能够达到AGV系统的最优性能指标。
根据一实施例，AGV调度有关参数的阈值包括与生产设备的剩余物料处理时间相对应的第一阈值以及与AGV的剩余电量相对应的第二阈值中的一者或两者，并且其中相关性能指标包括AGV利用率以及产线产率中的一者或两者。该实施例是AGV调度有关参数的阈值和相关性能指标的优选示例。AGV利用率以及产线产率是优选的目标，其中针对与生产设备的剩余物料处理时间相对应的第一阈值的优化能够从全局协同和优化AGV运输任务的生成及调度，从而防止产生对AGV运输需求的波峰和波谷；而针对与AGV的剩余电量相对应的第二阈值的优化能够优化AGV充电任务的生成，错开AGV充电时间段，防止产生AGV充电需求的波峰和波谷，减少AGV充电拥堵和充电等待。
根据另一实施例，在生产设备的剩余物料处理时间低于第一阈值的情况下，生成AGV运输任务以调度AGV向该生产设备供应物料，并且在AGV的剩余电量低于第二阈值的情况下，生成AGV充电任务以调度该AGV去往充电桩进行充电。通过上述第一阈值和第二阈值，能够在AGV系统中自动地且智能地生成AGV运输任务和AGV充电任务，从而能够更好地防止产生对AGV运输需求的波峰和波谷以及AGV充电需求的波峰和波谷。
根据又一实施例，相关性能指标的符合预设条件的所得值是与AGV利用率的最高值和/或产线产率的最高值。在该实施例中，给出了性能指标的优选示例，即AGV利用率以及产线产率的最高值。这使得能够在最大程度上利用AGV系统和生产设备，从而降低生产成本，提高成效。
根据又一实施例，对于生产设备中的至少一部分而言，所确定的与最高AGV利用率和/或最高产线产率相对应的第一阈值的取值是不同的；和/或对于AGV中的至少一部分而言，所确定的与最高AGV利用率和/或最高产线产率相对应的第二阈值的取值是不同的。在该实施例中，通过针对每一AGV和/或生产设备设定不同的阈值取值，充分考虑了各个AGV和/或生产设备的初始条件(诸如电量、已工作时间、磨损等等)的不同，因此使得最终获得的针对每一AGV和/或生产设备的阈值取值能够充分反映实际系统中的情形，从而能够针对该实际系统达到其最优的产线产率和/ 或AGV利用率。
上述说明仅是本申请技术方案的概述，为了能够更清楚了解本申请的技术手段，而可依照说明书的内容予以实施，并且为了让本申请的上述和其它目的、特征和优点能够更明显易懂，以下特举本申请的具体实施方式。
附图说明
为了更清楚地说明本申请实施例的技术方案，下面将对本申请实施例中所需要使用的附图作简单地介绍，显而易见地，下面所描述的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据附图获得其他的附图。
图1是根据本申请的一个实施例的AGV调度方法的示例流程图；
图2是根据本申请的一个实施例的阈值最优取值的获取方法的示例流程图；以及
图3是根据本申请的一个实施例的AGV系统的示意性框图。
在附图中，附图并未按照实际的比例绘制。
具体实施方式
下面将结合附图对本申请技术方案的实施例进行详细的描述。以下实施例仅用于更加清楚地说明本申请的技术方案，因此只作为示例，而不能以此来限制本申请的保护范围。
除非另有定义，本文所使用的所有的技术和科学术语与属于本申请的技术领域的技术人员通常理解的含义相同；本文中所使用的术语只是为了描述具体的实施例的目的，不是旨在于限制本申请；本申请的说明书和权利要求书及上述附图说明中的术语“包括”和“具有”以及它们的任何变形，意图在于覆盖不排他的包含。
在本申请实施例的描述中，技术术语“第一”“第二”等仅用于区别不同对象，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量、特定顺序或主次关系。在本申请实施例的描述中，“多 个”的含义是两个以上，除非另有明确具体的限定。
在本文中提及“实施例”意味着，结合实施例描述的特定特征、结构或特性可以包含在本申请的至少一个实施例中。在说明书中的各个位置出现该短语并不一定均是指相同的实施例，也不是与其它实施例互斥的独立的或备选的实施例。本领域技术人员显式地和隐式地理解的是，本文所描述的实施例可以与其它实施例相结合。
在本申请实施例的描述中，术语“和/或”仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本文中字符“/”，一般表示前后关联对象是一种“或”的关系。
发明人认识到，作为物流系统的一个重要组成部分，AGV系统有着可以替代人工搬运和精准柔性配送的作用。其中，作为AGV的决策系统，AGV系统所包括的调度控制器负责AGV运输任务分配、路径规划和调度、和/或充电管理等功能。在AGV系统的工作过程中，需要使用与多个AGV调度有关参数相关联的阈值来作为触发条件，以触发相应的工作任务。例如，AGV调度系统将根据生产设备的剩余物料处理时间来生成AGV运输任务，并将所生成的AGV运输任务分配给不同的AGV，并对AGV进行相应的路径规划和调度，来为生产设备运送生成物料；当AGV电量低过一些既定的阈值时，AGV调度控制系统会生成AGV充电任务，指派该AGV到相应充电桩进行充电；诸如此类。
然而，现有的AGV调度控制系统针对这些阈值都是使用由人为规定的固定阈值，既没有考虑实际生产情况的需要，也没有进行相应的阈值优化设计，从而没有优化和提升AGV系统的各种相关性能指标(诸如AGV利用率和产线产率(即生产设备的生产率))。例如，这种人为规定的固定阈值可能会导致设备停机待料情况，从而降低产线产率；或者会导致AGV充电拥堵和充电等待，降低AGV利用率；等等。
基于以上考虑，为了优化AGV系统的所需性能指标(诸如AGV利用率和产线产率)，本申请提供了一种AGV系统以及AGV调度方法，能够优化AGV系统中的各AGV的调度，从而获得最优的所需性能指标。
以下实施例为了方便说明，以针对动力电池的密封钉焊接缺陷样本生成为例进行说明。
根据本申请的一个实施例，参照图1，图1是根据本申请的一个实施例的AGV调度方法100的示例流程图。如图1中所示，方法100开始于步骤110，在此获取AGV调度有关参数的阈值的最优取值。在一实施例中，阈值的最优取值能够使得AGV系统的相关性能指标达到最优。根据一实施例，相关性能指标可包括AGV利用率以及产线产率中的一者或两者。由此，AGV调度有关参数的阈值的最优取值将使得AGV利用率和/或产线产率达到最优。
在另一实施例中，AGV调度有关参数的阈值可包括与生产设备的剩余物料处理时间相对应的第一阈值以及与AGV的剩余电量相对应的第二阈值中的一者或两者。在该实施例中，与生产设备的剩余物料处理时间相对应的第一阈值的最优取值将能够从全局协同和优化AGV运输任务的生成及调度，从而防止产生对AGV运输需求的波峰和波谷；而与AGV的剩余电量相对应的第二阈值的最优取值能够优化AGV充电任务的生成，错开AGV充电时间段，防止产生AGV充电需求的波峰和波谷，减少AGV充电拥堵和充电等待。
进一步根据该实施例，第一阈值被用于生成和调度AGV运输任务，即在生产设备的剩余物料处理时间低于第一阈值的情况下，生成AGV运输任务以调度AGV向该生产设备供应物料；第二阈值被用于生成和调度AGV充电任务，即在AGV的剩余电量低于第二阈值的情况下，生成AGV充电任务以调度该AGV去往充电桩进行充电。本领域技术人员可以明白，上述阈值仅仅是AGV系统中所使用的参数阈值的示例，还可以存在各种其他合适的参数阈值(诸如生产设备所产出的产品在产线上的积压量)并且它们都可以根据本申请的方法和系统来被优化和应用，在此不再赘述。
通过上述第一阈值和第二阈值，能够在AGV系统中自动地且智能地生成AGV运输任务和AGV充电任务，从而能够更好地防止产生对AGV运输需求的波峰和波谷以及AGV充电需求的波峰和波谷，由此可以 提高AGV利用率和产线产率。
在一实施例中，获取AGV调度有关参数的阈值的最优取值可以按任何合适的方式来执行。例如，图2示出了获取方式的一个示例。
参考图2，其示出了根据本申请的一个实施例的阈值最优取值的获取方法200的示例流程图。可以看到，方法200开始于步骤102，在此通过预先建立的针对实际AGV系统的仿真模型，针对AGV调度有关参数的阈值的不同取值进行仿真，以确定在阈值的相应取值下相关性能指标的所得值。
在一实施例中，仿真是借助于Plant Simulation或Flexsim仿真软件来执行的。在该实施例中，通过使用普通的仿真软件，能够更方便且快捷地执行本申请的方法。例如，通过使用仿真软件Plant Simulation构建AGV系统(以及任何所需的上位/下位系统)的仿真模型(至少包括AGV任务生成、AGV任务分配、AGV路径规划和调度、充电管理等模块)，并在仿真模型中定义需要优化的阈值(诸如与生产设备的剩余物料处理时间相对应的阈值以及与AGV的剩余电量相对应的阈值)和性能指标(诸如AGV利用率和/或产线产率)，随后针对每一组阈值取值，确保AGV任务分配、路径规划和调度等模块保持不变，通过Plant Simulation仿真算出性能指标。随后可基于所算出的性能指标来确定其中最优的性能指标，并进而获得与该最优的性能指标相对应的一组阈值取值。
在一优选实施例中，AGV调度有关参数的阈值可包括与生产设备的剩余物料处理时间相对应的第一阈值以及与AGV的剩余电量相对应的第二阈值中的一者或两者。在该实施例中，仿真可根据以下各个因素中的至少一者来进行以确定相关性能指标的所得值：工单数量、AGV数量、生产设备数量、生产设备的物料处理速率、AGV运力、AGV移动速度、AGV初始电量、AGV数量与AGV充电桩数目的比值、AGV充电速率，等等。将明白，还可存在影响第一阈值和/或第二阈值或者各种其他不同的AGV调度有关参数的阈值的任何其他合适因素，在此不再赘述。在该实施例中，对最优阈值取值的找出过程中所使用的参数的这一限定给出了对阈值取值有影响的各个因素，从而使得所找出的阈值取值更能够反映真实 AGV系统的状况，并能够达到真实系统的所需最优性能指标(诸如AGV利用率和/或产线产率)。
进一步根据该实施例，工单数量越多、AGV数量越少、生产设备的生产速率越低、AGV的运力越高、AGV的移动速度越快，则第一阈值的最优取值越小。在该实施例中，通过对影响第一阈值的优选参数进行选择，并进一步给出这些优选参数对第一阈值的具体影响，能够更快地找出阈值的最优取值，且使得所找出的最优取值更能够反映真实AGV系统的状况，并能够达到真实系统的所需最优性能指标(诸如AGV利用率和/或产线产率)。
进一步根据该实施例，工单数量越多、AGV数量与AGV充电桩数目的比值越大、AGV的充电速率越快、AGV的移动速度越快，则第二阈值的最优取值越小。在该实施例中，通过对影响第二阈值的优选参数进行选择，并进一步给出这些优选参数对第二阈值的具体影响，能够更快地找出阈值的最优取值，且使得所找出的最优取值更能够反映真实AGV系统的状况，并能够达到真实系统的所需最优性能指标(诸如AGV利用率和/或产线产率)。
在AGV调度有关参数的阈值可包括与生产设备的剩余物料处理时间相对应的第一阈值以及与AGV的剩余电量相对应的第二阈值中的一者或两者的实施例中，为了缩短仿真时间，仿真可针对与第一阈值相对应的第一范围中的值和/或与第二阈值相对应的第二范围中的值来确定相应的产线产率。在该实施例中，通过对仿真过程中的阈值取值范围的限定，使得能够在合需的范围内对阈值进行仿真，从而缩短仿真时间，更高效地找出合需的阈值取值。
进一步根据以上实施例，第一范围的下限是基于AGV的运力和生产设备的物料处理速率来计算得到的，并且第一范围的上限是基于AGV的运力、生产设备的物料处理速率以及生产设备的物料存储容量来计算得到的。在该实施例中，通过对第一阈值的取值范围的进一步限定，使得能够在更大的程度上缩小需要仿真的阈值取值范围，从而在更大程度上缩短仿真时间，更高效地找出合需的阈值取值。进一步根据该实施例，第二范 围的下限是基于AGV的当前位置、AGV的移动速度以及充电桩的位置来计算得到的。在该实施例中，通过对第二阈值的取值范围的进一步限定，使得能够在更大的程度上缩小需要仿真的阈值取值范围，从而在更大程度上缩短仿真时间，更高效地找出合需的阈值取值。
在一实施例中，相关性能指标的符合预设条件的所得值是与AGV利用率的最高值和/或产线产率的最高值。在该实施例中，给出了性能指标的优选示例，即AGV利用率以及产线产率的最高值。这使得能够在最大程度上利用AGV系统和生产设备，从而降低生产成本，提高成效。
在又一实施例中，对于生产设备中的至少一部分而言，所确定的与最高AGV利用率和/或最高产线产率相对应的第一阈值是不同的；和/或对于AGV中的至少一部分而言，所确定的与最高AGV利用率和/或最高产线产率相对应的第二阈值是不同的。在该实施例中，并非针对每一AGV和/或生产设备采用相同的阈值取值，而是通过针对每一AGV和/或生产设备设定不同的阈值取值，充分考虑了各个AGV和/或生产设备的初始条件(诸如电量、已工作时间、磨损等等)的不同，因此使得最终获得的针对每一AGV和/或生产设备的阈值取值能够充分反映实际系统中的情形，从而能够针对该实际系统达到其最优的产线产率和/或AGV利用率。
继续参考图2，在步骤104，方法200可包括取与相关性能指标的符合预设条件的所得值相对应的AGV调度有关参数的阈值的取值作为AGV调度有关参数的阈值的最优取值。
将明白，可以存在各种其他合适的方式来得到AGV调度有关参数的阈值的最优取值，例如通过查找预先确立的表(基于实际AGV系统的初始条件来确立)、通过内插(外插)等等方式，在此不再赘述。
回头参考图1，在步骤120，方法100可包括在实际AGV系统中应用AGV调度有关参数的阈值的最优取值来进行AGV调度。由此，通过这一AGV调度方法100，可以(例如在规划阶段)仿真出与AGV系统的所考虑的不同性能指标的最优值相对应的调度参数阈值取值，由此可以在实际的AGV系统中使用所得到的调度参数阈值取值，从而能够达到AGV系统的最优性能指标。
图3是根据本申请的一个实施例的AGV系统300的示意性框图。
参考图3，可以看到，AGV系统300可包括AGV调度控制器310、AGV 320、以及AGV仿真系统330。将明白，AGV调度控制器310、AGV 320、以及AGV仿真系统330可以是能够彼此通信的，如图3中所示的闪电形状所示。当然，这一通信可以采用任何其他合适的形式，诸如AGV 310与AGV仿真系统330可不直接图像，而是可经由AGV调度控制器310作为中介来进行通信，诸如此类。
本领域技术人员可以明白，尽管图3中为简明起见仅示出了一个AGV 310，AGV系统300可包括任意数量的AGV，如图3中的省略号340所示。此外，尽管图3中以服务器的形式示出了AGV调度控制器310，本领域技术人员将明白，这仅仅是示例，AGV调度控制器310可以采取任何合适的形式，诸如在云上。
在一实施例中，AGV仿真系统330可被配置成获取AGV调度有关参数的阈值的最优取值。进一步根据该实施例，这可包括通过预先建立的针对实际AGV系统300的仿真模型，针对AGV调度有关参数的阈值的不同取值进行仿真，以确定在阈值的相应取值下相关性能指标的所得值；以及取与相关性能指标的符合预设条件的所得值相对应的AGV调度有关参数的阈值的取值作为AGV调度有关参数的阈值的最优取值。随后，AGV调度控制器310可被配置成从AGV仿真系统330接收并应用该最优取值来调度AGV 320。如此，通过AGV系统300，可以(例如在规划阶段)仿真出与AGV系统的所考虑的不同性能指标的最优值相对应的调度参数阈值取值，由此可以在实际的AGV系统中使用所得到的调度参数阈值取值，从而能够达到AGV系统的最优性能指标。
根据另一实施例，AGV调度有关参数的阈值可包括与生产设备的剩余物料处理时间相对应的第一阈值以及与AGV的剩余电量相对应的第二阈值中的一者或两者，并且其中相关性能指标包括AGV利用率以及产线产率中的一者或两者。该实施例是AGV调度有关参数的阈值和相关性能指标的优选示例。AGV利用率以及产线产率是优选的目标，其中针对与生产设备的剩余物料处理时间相对应的第一阈值的优化能够从全局协同和 优化AGV运输任务的生成及调度，从而防止产生对AGV运输需求的波峰和波谷；而针对与AGV的剩余电量相对应的第二阈值的优化能够优化AGV充电任务的生成，错开AGV充电时间段，防止产生AGV充电需求的波峰和波谷，减少AGV充电拥堵和充电等待。
根据另一实施例，在生产设备的剩余物料处理时间低于第一阈值的情况下，生成AGV运输任务以调度AGV向该生产设备供应物料，并且在AGV的剩余电量低于第二阈值的情况下，生成AGV充电任务以调度该AGV去往充电桩进行充电。通过上述第一阈值和第二阈值，能够在AGV系统中自动地且智能地生成AGV运输任务和AGV充电任务，从而能够更好地防止产生对AGV运输需求的波峰和波谷以及AGV充电需求的波峰和波谷。
根据又一实施例，相关性能指标的符合预设条件的所得值是与AGV利用率的最高值和/或产线产率的最高值。在该实施例中，给出了性能指标的优选示例，即AGV利用率以及产线产率的最高值。这使得能够在最大程度上利用AGV系统和生产设备，从而降低生产成本，提高成效。
在又一实施例中，对于生产设备中的至少一部分而言，所确定的与最高AGV利用率和/或最高产线产率相对应的第一阈值是不同的；和/或对于AGV中的至少一部分而言，所确定的与最高AGV利用率和/或最高产线产率相对应的第二阈值是不同的。在该实施例中，并非针对每一AGV和/或生产设备采用相同的阈值取值，而是通过针对每一AGV和/或生产设备设定不同的阈值取值，充分考虑了各个AGV和/或生产设备的初始条件(诸如电量、已工作时间、磨损等等)的不同，因此使得最终获得的针对每一AGV和/或生产设备的阈值取值能够充分反映实际系统中的情形，从而能够针对该实际系统达到其最优的产线产率和/或AGV利用率。
尽管图3中将AGV调度控制器310和AGV仿真系统330示为分开的组件，但本领域技术人员将明白，它们可以位于一处或者它们可以各自拆分成多个子系统(只要这些子系统能够实现所述功能即可)。
本申请的技术方案能够优化与生产设备的剩余物料处理时间相关的阈值。当生产设备的剩余物料处理时间低于该阈值时,AGV系统的相关 AGV调度控制器会将AGV运输任务自动指派给AGV系统中的一个或多个所选AGV来进行物料运输。
本申请的技术方案还能够优化与AGV的剩余电量相关的阈值。当AGV的剩余电量低于该阈值时，AGV系统的相关AGV调度控制器会自动生成针对该AGV的充电任务并指派该AGV到相应充电桩进行充电。
本申请的技术方案可以在规划阶段，通过AGV系统仿真和调用优化算法库，来优化与生产设备的剩余物料处理时间相关的阈值和与AGV的剩余电量相关的阈值，以便自动化和智能化地生成和调度AGV运输任务和AGV充电任务，从而能够在全局上协同和优化AGV的利用率并提高产线产率。
将明白，本申请的技术方案可以在AGV系统的规划阶段预先地和/或在实际系统的工作过程中执行。
虽然已经参考优选实施例对本申请进行了描述，但在不脱离本申请的范围的情况下，可以对其进行各种改进并且可以用等效物替换其中的部件。尤其是，只要不存在结构冲突，各个实施例中所提到的各项技术特征均可以任意方式组合起来。本申请并不局限于文中公开的特定实施例，而是包括落入权利要求的范围内的所有技术方案。

Claims (17)

  1. 一种AGV调度方法，包括：
    获取AGV调度有关参数的阈值的最优取值，包括：
    通过预先建立的针对实际AGV系统的仿真模型，针对所述AGV调度有关参数的阈值的不同取值进行仿真，以确定在所述阈值的相应取值下相关性能指标的所得值；以及
    取与所述相关性能指标的符合预设条件的所得值相对应的AGV调度有关参数的阈值的取值作为所述AGV调度有关参数的阈值的最优取值；以及
    在所述实际AGV系统中应用所述AGV调度有关参数的阈值的最优取值来进行AGV调度。
  2. 根据权利要求1所述的方法，其中所述AGV调度有关参数的阈值包括与生产设备的剩余物料处理时间相对应的第一阈值以及与AGV的剩余电量相对应的第二阈值中的一者或两者，并且其中所述相关性能指标包括AGV利用率以及产线产率中的一者或两者。
  3. 根据权利要求1-2中的任一项所述的方法，其中在生产设备的剩余物料处理时间低于所述第一阈值的情况下，生成AGV运输任务以调度AGV向该生产设备供应物料，并且在AGV的剩余电量低于所述第二阈值的情况下，生成AGV充电任务以调度该AGV去往充电桩进行充电。
  4. 根据权利要求1-3中的任一项所述的方法，其中所述仿真根据以下各个因素中的至少一者来进行以确定所述相关性能指标的所得值：工单数量、AGV数量、生产设备数量、生产设备的物料处理速率、AGV运力、AGV移动速度、AGV初始电量、AGV数量与AGV充电桩数目的比值、AGV充电速率。
  5. 根据权利要求1-4中的任一项所述的方法，其中工单数量越多、AGV数量越少、生产设备的生产速率越低、AGV的运力越高、AGV的移动速度越快，则所述第一阈值的最优取值越小。
  6. 根据权利要求1-5中的任一项所述的方法，其中工单数量越多、AGV数量与AGV充电桩数目的比值越大、AGV的充电速率越快、AGV的移动速度越快，则所述第二阈值的最优取值越小。
  7. 根据权利要求1-6中的任一项所述的方法，其中所述仿真针对与所述第一阈值相对应的第一范围中的值和/或与所述第二阈值相对应的第二范围中的值来确定相应的产线产率。
  8. 根据权利要求1-7中的任一项所述的方法，其中所述第一范围的下限是基于AGV的运力和生产设备的物料处理速率来计算得到的，并且所述第一范围的上限是基于AGV的运力、生产设备的物料处理速率以及生产设备的物料存储容量来计算得到的。
  9. 根据权利要求1-8中的任一项所述的方法，其中所述第二范围的下限是基于AGV的当前位置、AGV的移动速度以及充电桩的位置来计算得到的。
  10. 根据权利要求1-9所述的方法，其中，
    所述相关性能指标的符合预设条件的所得值是与AGV利用率的最高值和/或产线产率的最高值。
  11. 根据权利要求1-10中的任一项所述的方法，其中，
    对于生产设备中的至少一部分而言，所确定的与最高AGV利用率和/或最高产线产率相对应的第一阈值的取值是不同的；和/或
    对于AGV中的至少一部分而言，所确定的与最高AGV利用率和/或最高产线产率相对应的第二阈值的取值是不同的。
  12. 根据权利要求1-11中的任一项所述的方法，其中所述仿真是借助于Plant Simulation或Flexsim仿真软件来执行的。
  13. 一种AGV系统，包括：
    AGV；
    AGV仿真系统，所述AGV仿真系统被配置成获取AGV调度有关参数的阈值的最优取值，包括：
    通过预先建立的针对实际AGV系统的仿真模型，针对所述AGV调度有关参数的阈值的不同取值进行仿真，以确定在所述阈值的相应取值下相关性能指标的所得值；以及
    取与所述相关性能指标的符合预设条件的所得值相对应的AGV调度有关参数的阈值的取值作为所述AGV调度有关参数的阈值的最优取值；以及
    AGV调度控制器，所述AGV调度控制器被配置成应用所述AGV调度有关参数的阈值的最优取值来调度所述AGV。
  14. 根据权利要求13所述的系统，其中所述AGV调度有关参数的阈值包括与生产设备的剩余物料处理时间相对应的第一阈值以及与AGV的剩余电量相对应的第二阈值中的一者或两者，并且其中所述相关性能指标包括AGV利用率以及产线产率中的一者或两者。
  15. 根据权利要求13或14所述的系统，其中在生产设备的剩余物料处理时间低于所述第一阈值的情况下，生成AGV运输任务以调度AGV向该生产设备供应物料，并且在AGV的剩余电量低于所述第二阈值的情况下，生成AGV充电任务以调度该AGV去往充电桩进行充电。
  16. 根据权利要求13-15中的任一项所述的系统，其中，
    所述相关性能指标的符合预设条件的所得值是与AGV利用率的最高值和/或产线产率的最高值。
  17. 根据权利要求13-16中的任一项所述的系统，其中，
    对于生产设备中的至少一部分而言，所确定的与最高AGV利用率和/或最高产线产率相对应的第一阈值的取值是不同的；和/或
    对于AGV中的至少一部分而言，所确定的与最高AGV利用率和/或最高产线产率相对应的第二阈值的取值是不同的。
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CN107179769A (zh) * 2017-06-06 2017-09-19 泉州装备制造研究所 一种基于实时调度仿真和排队论的agv数量配置方法
WO2019142499A1 (ja) * 2018-01-17 2019-07-25 村田機械株式会社 シミュレーションシステム、およびシミュレート方法
CN110187647A (zh) * 2018-02-23 2019-08-30 北京京东尚科信息技术有限公司 模型训练方法及系统
CN112084580A (zh) * 2020-09-14 2020-12-15 西南交通大学 基于回归分析和满意度函数法的agv系统优化配置方法

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WO2019142499A1 (ja) * 2018-01-17 2019-07-25 村田機械株式会社 シミュレーションシステム、およびシミュレート方法
CN110187647A (zh) * 2018-02-23 2019-08-30 北京京东尚科信息技术有限公司 模型训练方法及系统
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