An automatic material replenishment method for a production line based on multi-AGV collaborative handling

Abstract

The present application provides an automatic material replenishment method for a production line based on multi-AGV collaborative handling, the method comprising obtaining the material types of multiple required materials and the total required quantity of each material in response to a production target; generating a scheduling plan for each material and scheduling work information corresponding to the scheduling plan according to the material type, the total required quantity, the obtained produced quantity and equipment working information; determining the time required for the next replenishment of each material according to the material type and the scheduling work information based on a time optimization model; determining the production progress of each material according to the material type, the total required quantity, the time required for the next replenishment and the produced quantity based on a material balance model; determining a target scheduling plan from the scheduling plans for each material in the multiple required materials and the multiple scheduling plans after the scheduling plan is updated according to the time required for the next replenishment of each material and the production progress of each material.

Description

Technical Field

[0001] The present application relates to the field of intelligent logistics technology, and in particular to an automatic material replenishment method for a production line based on multi-AGV collaborative handling. Background Art

[0002] In logistics and manufacturing, the automatic refilling system of the automated production line is used for the storage and handling of materials. The automatic refilling system of the automated production line needs to quickly and accurately complete tasks such as material handling, stacking and refilling of production lines.

[0003] In order to improve the execution efficiency and accuracy of the automatic replenishment system of the automated production line, a real-time optimization method for material distribution in an uncertain workshop environment based on DQN (publication number CN113128770A) is currently proposed, which provides a real-time optimization method for material distribution based on disturbance factors in two stages, the material demand stage and the distribution stage, to improve the accuracy of material distribution. However, in the calculation process of material demand, this optimization method only considers the disturbance factors that affect the processing time of the workstation, that is, this optimization method only reduces the idle time of the workstation by calculating the travel time of the transport vehicle (Automated Guided Vehicle, AGV) and the remaining working time of the workstation to improve the distribution efficiency. In this way, only the distribution of a single material in the workshop is considered, and the coordinated distribution of different types of materials in the actual workshop cannot be achieved.

[0004] A material distribution scheduling method and system considering batching errors (publication number CN112801484A) further considers the probability of various batching errors occurring at each workstation during the material demand stage, that is, further considers the order of different types of materials at the workstation, and distributes materials based on the order of materials. However, this distribution scheduling method solves the problem of the order in which the workstations should replenish materials and how to eliminate the errors that may occur during replenishment, and cannot effectively reduce the production time of the entire production task. At the same time, this distribution scheduling method is only applicable to scenarios where the order of materials at the workstations is predetermined.

[0005] In view of this, there is an urgent need for a method that can shorten the production time of the entire production task while meeting the synchronization of production progress between various materials in the production target, and an automatic feeding system for the production line using this method. Summary of the invention

[0006] The present application provides an automatic material replenishment method for a production line based on multi-AGV collaborative handling, so as to shorten the production time of the production tasks of the entire production line replenishment system while meeting the synchronization of production progress between various materials in the production target.

[0007] The first aspect of the present application provides a production line automatic material replenishment method based on multi-AGV collaborative handling, which is applied to the production line automatic material replenishment system. The method includes: obtaining the material types of multiple required materials generated in response to the production target, and the total required quantity of each material in the multiple required materials; obtaining the equipment working information of the production line automatic material replenishment system and the produced quantity of each material in the multiple required materials; generating a scheduling plan for each material according to the material type, the total required quantity, the produced quantity and the equipment working information, and the scheduling work information corresponding to the scheduling plan; Based on the time optimization model, the time required for the next replenishment of each material is determined according to the material type and scheduling work information. The time optimization model takes the minimum time required for the next replenishment of each material as the optimization target and is constructed according to the objective function; based on the material balance model, the production progress of each material is determined according to the material type, the total demand quantity, the time required for the next replenishment and the produced quantity. The material balance model takes the ratio between the production progresses of multiple required materials within a preset ratio range as the optimization target and is constructed according to the objective function; according to the time required for the next replenishment of each material and the production progress of each material, a target scheduling plan is determined from the scheduling plans of each material among the multiple required materials and the multiple scheduling plans after the scheduling plans are updated. The target scheduling plan instructs the idle AGVs among the multiple AGVs in the automatic replenishment system of the production line to transport the target material among the multiple required materials from the target material storage place to the target production line among the multiple production lines according to the target driving path.

[0008] In some embodiments of the first aspect, a target scheduling scheme is determined from the scheduling schemes of each material among the multiple required materials and the multiple scheduling schemes after the scheduling schemes are updated according to the time required for the next replenishment of each material and the production progress of each material, including: determining the fitness value corresponding to the scheduling scheme of each material according to the time required for the next replenishment of each material and the production progress of each material, and updating the scheduling scheme and the scheduling work information corresponding to the scheduling scheme, and then re-executing the steps of determining the next replenishment time of each material based on the time optimization model according to the material type and the scheduling work information, to updating the scheduling scheme and the scheduling work information corresponding to the scheduling scheme; until the update stop condition is met, obtaining multiple groups of scheduling schemes corresponding to the multiple required materials, each group of scheduling schemes in the multiple groups of scheduling schemes including the scheduling scheme of each material, and the multiple scheduling schemes after the scheduling scheme is updated; determining the target scheduling scheme according to the scheduling scheme of each material, and the multiple fitness values ​​corresponding to the multiple scheduling schemes after the scheduling scheme is updated.

[0009] In some embodiments of the first aspect, the expression of the time optimization model is as follows:

[0010]

[0011] in, Indicates the time required for the next replenishment of the specified material. The specified material is the material of the scheduling plan. represents the average driving speed of the specified AGV in the scheduling work information, Indicates the distance from the designated AGV to the designated material storage location obtained according to the scheduling work information, Indicates the distance from the designated material storage location to the designated production line of the designated AGV obtained according to the scheduling work information, represents the coefficient of the crossover penalty, represents the number of intersections between the driving path of the specified AGV and the driving paths of other AGVs obtained according to the scheduling work information, Indicates the type of material, and They respectively represent the remaining workload and processing speed of the robot arm in processing the specified material in the scheduling work information, k represents the kth material, i and j are used to indicate the location point on the map, and n and m are used to represent the size of the map.

[0012] In some embodiments of the first aspect, the expression of the material balance model is as follows:

[0013]

[0014] in, Indicates the production progress of the specified material. Indicates the quantity of the specified material produced. Indicates the total required quantity of the specified material. Indicates the type of material. Indicates the remaining workload of the robot arm in processing the specified material in the scheduling work information. Indicates the time required for the next refill of the specified material. Indicates the penalty amount for the specified material.

[0015] In some embodiments of the first aspect, a target scheduling scheme is determined based on a scheduling scheme for each material and multiple fitness values ​​corresponding to multiple scheduling schemes after the scheduling scheme is updated, including: based on the scheduling scheme for each material and multiple fitness values ​​corresponding to multiple scheduling schemes after the scheduling scheme is updated, determining the scheduling scheme corresponding to the minimum fitness value among the multiple fitness values ​​as the target scheduling scheme, wherein the time required for the next replenishment of each material and the production progress of each material are directly proportional to the fitness value, respectively.

[0016] In some embodiments of the first aspect, the method further includes, when scheduling plans and scheduling work information corresponding to the scheduling plans are updated for multiple required materials respectively, and scheduling execution obstacle information is obtained, adjusting the scheduling plan for each material according to the scheduling execution obstacle information.

[0017] In some embodiments of the first aspect, a scheduling plan for each material is generated according to the material type, total demand quantity, produced quantity and equipment working information, including: determining the unsaturated materials of multiple required materials according to the total demand quantity, produced quantity and material type; according to the octopus algorithm, regarding the idle AGV and unsaturated materials in the equipment working information as the first tentacle and the second tentacle, respectively; simulating the first selection of the unsaturated materials by the first tentacle and the second selection of the multiple production lines in the equipment working information by the second tentacle, to generate multiple octopuses, each of the multiple octopuses representing a scheduling plan for each material.

[0018] In some embodiments of the first aspect, when scheduling schemes and scheduling work information corresponding to the scheduling schemes are respectively updated for a plurality of required materials, and scheduling execution obstruction information is obtained, the scheduling scheme of each material is adjusted according to the scheduling execution obstruction information, including: according to the octopus algorithm, the updating process of the scheduling schemes and scheduling work information corresponding to the scheduling schemes for the plurality of required materials is regarded as a process in which the second tentacle of each of the plurality of octopuses performs a plurality of second selections on the plurality of production lines in the equipment work information; when performing the plurality of second selections, simulating that the second tentacle of each octopus finds the scheduling execution obstruction information, the scheduling execution obstruction information is shared with other octopuses in the plurality of octopuses;

[0019] Other octopuses adjust the second tentacle's next second choice of the production line in the equipment work information according to the scheduling execution obstacle information;

[0020] The first selection of the unsaturated material by the first tentacle of each octopus in the multiple octopuses and the next second selection of the production line in the equipment working information by the adjusted second tentacle are regarded as the adjusted scheduling plan for each material.

[0021] In some embodiments of the first aspect, the method further includes, when there is saturated material and it is determined that the saturated material is placed on a production line of an automatic replenishment system of the production line, controlling an idle AGV among the multiple AGVs to transport the saturated material back to the warehouse.

[0022] A second aspect of the present application provides an automatic material replenishment system for a production line, the automatic material replenishment system for the production line comprising a control device, a plurality of AGVs and a plurality of production lines, the control device being used to obtain the material types of a plurality of required materials generated in response to a production target, and the total required quantity of each of the plurality of required materials; obtain equipment working information of the automatic material replenishment system for the production line and the produced quantity of each of the plurality of required materials; generate a scheduling plan for each material, and scheduling work information corresponding to the scheduling plan, according to the material type, the total required quantity, the produced quantity and the equipment working information; Based on the time optimization model, the time required for the next replenishment of each material is determined according to the material type and scheduling work information. The time optimization model takes the minimum time required for the next replenishment of each material as the optimization target and is constructed according to the objective function; based on the material balance model, the production progress of each material is determined according to the material type, the total demand quantity, the time required for the next replenishment and the produced quantity. The material balance model takes the ratio between the production progresses of multiple required materials within a preset ratio range as the optimization target and is constructed according to the objective function; according to the time required for the next replenishment of each material and the production progress of each material, a target scheduling plan is determined from the scheduling plans of each material among the multiple required materials and the multiple scheduling plans after the scheduling plans are updated. The target scheduling plan instructs the idle AGVs among the multiple AGVs in the automatic replenishment system of the production line to transport the target material among the multiple required materials from the target material storage place to the target production line among the multiple production lines according to the target driving path.

[0023] It can be understood that the automatic material replenishment method, automatic material replenishment system and control device of the automatic material replenishment system of the production line based on multi-AGV collaborative handling provided by the present application determine the time required for the next material replenishment of each material according to the material type and scheduling work information through a time optimization model constructed with the minimum time required for the next material replenishment of each material as the optimization target. And by taking the ratio between the production progress of multiple required materials within a preset ratio range as the optimization target, a material balance model constructed according to the objective function is used to determine the production progress of each material according to the material type, total demand quantity, time required for the next material replenishment and the quantity produced. At the same time, the minimum time required for the automatic material replenishment system of the production line to execute the next material replenishment and the balance between the production progress of multiple required materials in the production target are taken into account.

[0024] Finally, according to the time required for the next replenishment of each material and the production progress of each material, the target scheduling plan is determined from the scheduling plans for each material among the multiple required materials and the multiple scheduling plans after the scheduling plans are updated. The target scheduling plan can shorten the production time of the production tasks of the automatic replenishment system of the entire production line while meeting the synchronization of the production progress between various materials in the production goals. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0026] Figure 1 A schematic diagram of the structure of the automatic feeding system of the production line provided in the embodiment of the present application;

[0027] Figure 2 A schematic diagram of a process flow of a production line automatic material replenishment method based on multi-AGV collaborative handling provided in an embodiment of the present application;

[0028] Figure 3 An application scenario diagram of a production line automatic material replenishment method based on multi-AGV collaborative handling provided in an embodiment of the present application;

[0029] Figure 4 Another application scenario diagram of the production line automatic material replenishment method based on multi-AGV collaborative handling provided in an embodiment of the present application;

[0030] Figure 5 Another schematic diagram of a process flow of a production line automatic material replenishment method based on multi-AGV collaborative handling provided in an embodiment of the present application;

[0031] Figure 6 A schematic diagram of a control device for an automatic feeding system of a production line provided in an embodiment of the present application;

[0032] Figure 7 Another structural schematic diagram of the control device of the automatic feeding system of the production line provided in an embodiment of the present application.

[0033] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0034] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0035] The terms "first", "second", etc. involved in this application are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features.

[0036] See also Figure 1 , Figure 1 A structural schematic diagram of the automatic material replenishment system for a production line provided in the present application, the automatic material replenishment system 100 for the production line includes a control device 10, multiple transport vehicles (Automated Guided Vehicle, AGV) 20 and multiple production lines 30, the control device 10 is used to determine a target scheduling plan according to the automatic material replenishment method for a production line based on multi-AGV collaborative transportation in the present application, and according to the target scheduling plan, control the idle AGV 20 among the multiple AGVs 20 to transport the target material among the multiple required materials from the target material storage place to the target production line 30 among the multiple production lines 30 according to the target driving path.

[0037] In some embodiments, the production line automatic material replenishment system 100 further includes a robot arm 40, which is used to process a variety of required materials. The robot arm 40 can process a variety of required materials on more than two production lines 30 at the same time.

[0038] In some embodiments, each AGV 20 is provided with a tray (not shown) and a depth camera (not shown), the tray is used to hold materials, and the depth camera is used to collect the position information of the tray. The control device 10 is also used to correct the placement angle of the tray according to the position information of the tray to accurately pick up the material.

[0039] In some embodiments, three conveyor lines 31 and four conveyor line guardrails 32 are provided on each production line 30. The depth camera of the AGV 20 is also used to obtain the position information of the vertices o1, o2, o3 and o4 of the four conveyor line guardrails 32. The control device 10 is also used to determine the posture of the three conveyor lines 31 according to the position information of the vertices o1, o2, o3 and o4 of the four conveyor line guardrails 32, and control the AGV 20 to accurately place the materials on the three conveyor lines 31 according to the posture of the three conveyor lines 31.

[0040] It should be noted that Figure 1 This is only a schematic diagram of a structure provided in the embodiment of the present application. Figure 1 The actual form of the various devices included in the Figure 1 The interaction mode between devices is limited, and in the specific application of the solution, it can be set according to actual needs.

[0041] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0042] Please combine Figure 1 and Figure 2 , Figure 2 1 is a flow chart of a production line automatic material replenishment method based on multi-AGV collaborative handling. The execution subject of the automatic material replenishment method may be a production line automatic material replenishment system 100, specifically, a control device 10. Figure 2 As shown, the automatic feeding method may include the following steps:

[0043] Step S110: Acquire the material types of multiple required materials generated in response to the production target, and the total required quantity of each of the multiple required materials.

[0044] Specifically, in one embodiment, Figure 1 As shown, the control device 10 is deployed with a Robot Control System (RCS). The production line automatic replenishment system 100 also includes a general control device (not shown), and the general control device is deployed with a Manufacturing Execution System (MES). The general control device deployed with the MES system generates the material types of multiple required materials and the total required quantity of each of the multiple required materials in response to the production target, and sends them to the control device 10 deployed with the RCS system. In another embodiment, the MES system is deployed in the control device 10 at the same time as the RCS system, and the control device 10 generates the material types of multiple required materials and the total required quantity of each of the multiple required materials in response to the production target.

[0045] Step S120: Acquire equipment operating information of the automatic material replenishment system of the production line and the produced quantity of each of the multiple required materials.

[0046] Equipment working information refers to the working information of each device in the automatic replenishment system 100 of the production line. Each device includes a robot arm 40, a production line 30, and an AGV 20. The equipment working information includes the number of each device, the location information of each device, the average driving speed and driving position of the AGV 20 and other driving information, the storage capacity of the production line 30, and the remaining workload and processing speed of the robot arm 40 for processing each material. Among them, a laser rangefinder (not shown) is set directly above each storage location on the production line 30. The laser rangefinder is used to sense the height of each storage location. If the height of the storage location is greater than the height threshold, it is determined that the storage location has materials stored, thereby determining the storage capacity of each production line 30. The remaining workload and processing speed of each material processed by each robot arm 40 are obtained by calculating the storage capacity of the multiple production lines 30 it is responsible for.

[0047] Step S130: Generate a scheduling plan for each material and scheduling work information corresponding to the scheduling plan based on the material type, total demand quantity, produced quantity and equipment working information.

[0048] The scheduling plan includes transporting the specified materials from the specified material storage location to the specified production line according to the specified driving path. The scheduling work information refers to the work information of each device required to implement the scheduling plan.

[0049] In one embodiment, a scheduling plan can be generated based on the Octopus Algorithm. First, unsaturated materials of multiple required materials are determined based on the total demand quantity, the produced quantity, and the material type. Then, according to the Octopus Algorithm, the idle AGV and unsaturated materials in the equipment working information are regarded as the first tentacle and the second tentacle, respectively. Simulate the first selection of the unsaturated material by the first tentacle and the second selection of the multiple production lines in the equipment working information by the second tentacle, and generate multiple octopuses, each of which represents a scheduling plan for each material.

[0050] For example, Figure 3 As shown, the unsaturated materials of the multiple required materials are determined to be material A and material B according to the total demand quantity, the produced quantity and the material type. The idle AGV is regarded as the first tentacle, and the material A and material B are regarded as the second tentacle. The first tentacle is simulated to make the first selection of material A and material B, and the second tentacle is simulated to make the second selection of any one of the first production line 1 to the third production line 3 among the multiple production lines, and two octopuses are generated, wherein one octopus (i.e., the scheduling scheme) is that the idle AGV transports material A from the material A storage to the first production line 1, and the other octopus (i.e., another scheduling scheme) is that the idle AGV transports material B from the material B storage to the fourth production line 4 among the multiple production lines.

[0051] It can be understood that the tentacles in the octopus algorithm, as decision points, can make independent choices based on associated information. In this implementation, the idle AGV and unsaturated materials in the equipment working information are regarded as the first tentacle (decision point 1) and the second tentacle (decision point 2), respectively. The idle AGV and unsaturated materials can make independent choices based on associated information to optimize the configuration of the scheduling plan.

[0052] After the scheduling plan is generated, the scheduling work information required by the scheduling plan is matched according to the equipment working information.

[0053] Step S140: Based on the time optimization model, determine the time required for the next replenishment of each material according to the material type and scheduling work information.

[0054] The time optimization model takes the minimum time required for the next refill of each material as the optimization target and is constructed based on the objective function. The next refill time refers to the time required to transport the specified material from the specified material storage location to the specified production line along the specified driving path.

[0055] It is understandable that since there are multiple required materials, multiple production lines and multiple driving routes, there are multiple scheduling schemes for AGV to transport multiple materials from the material storage to the production line. Through the time optimization model, the time required for the next replenishment of each material can be calculated, thereby preparing for the target scheduling scheme to obtain the minimum time required for the next replenishment in the subsequent steps.

[0056] Step S150: Based on the material balance model, the production progress of each material is determined according to the material type, the total required quantity, the time required for the next replenishment and the produced quantity.

[0057] The material balance model is constructed based on the objective function, with the ratio between the production progress of multiple required materials within the preset ratio range as the optimization target. It can be understood that when the ratio between the production progress of multiple required materials is within the preset ratio range, the production progress of multiple required materials is most balanced.

[0058] It can be understood that the production target requires the simultaneous processing of multiple required materials. Through the material balance model, the production progress of each material can be calculated, thereby preparing for the target scheduling plan for the target material with a slower production progress in the subsequent steps.

[0059] Step S160: determining a target scheduling plan from the scheduling plans for each material among the multiple required materials and the multiple scheduling plans after the scheduling plans are updated according to the time required for the next replenishment of each material and the production progress of each material.

[0060] Specifically, for each material, there are also multiple driving routes and multiple production lines to choose from, that is, each material corresponds to multiple scheduling plans. Therefore, after obtaining the initial material type, total demand quantity, produced quantity and equipment working information, and generating a scheduling plan for each material, through the selection of different driving routes and / or production lines and other equipment working information, multiple scheduling plans after the scheduling plan is updated, as well as the scheduling work information of the scheduling plan, can be obtained.

[0061] Next, for each scheduling plan, considering the time required for the next replenishment of the material corresponding to the scheduling plan and the production progress of the corresponding material, a target scheduling plan can be determined from multiple scheduling plans. The target scheduling plan minimizes the time required for the automatic replenishment system of the production line to execute the next replenishment while balancing the production progress among the multiple required materials.

[0062] See also Figure 4 In an application scenario, a material workshop is provided with an automatic material replenishment system for a production line. The material workshop includes a warehouse, a production area I, and a production area II. The warehouse is provided with a material storage area, and production area I is provided with three production lines of the automatic material replenishment system for the production line and a robotic arm responsible for the three production lines. Production area II is provided with two production lines of the automatic material replenishment system for the production line and a robotic arm responsible for the two production lines. The control device of the automatic material replenishment system for the production line obtains the material types A, B, and C of the three required materials generated in response to the production target, as well as the total required quantity a1 of material A, the total required quantity b1 of material B, and the total required quantity c1 of material C. The control device also obtains the working information of the AGV, the production line, and the robotic arm, and the produced quantity a2 of material A, the produced quantity b2 of material B, and the produced quantity c2 of material C.

[0063] Next, the control device generates a scheduling plan for material A and the scheduling work information corresponding to the scheduling plan based on the three types of materials, the total demand quantity a1, the produced quantity a2, and the working information of the AGV, production line and robotic arm. Similarly, the scheduling plan for materials B and C and the scheduling work information corresponding to the scheduling plan are obtained.

[0064] Next, the control device determines the time required for the next replenishment of material A based on the time optimization model according to the scheduling work information of the three material types and material A, and so on, obtains the time required for the next replenishment of materials B and C. And based on the material balance model, the production schedule of material A is determined according to the three material types, the total demand quantity a1, the time required for the next replenishment and the produced quantity a2, and so on, obtains the production schedule of materials B and C.

[0065] Finally, the control device scores the scheduling scheme of material A based on the time required for the next refill and the production progress of material A, and the multiple scheduling schemes updated by selecting different driving routes and / or production line equipment working information. Similarly, the scheduling schemes of materials B and C, as well as the updated multiple scheduling schemes, are scored, and a target scheduling scheme a is determined from all the scored scheduling schemes. 03 , the control device is based on the target scheduling scheme a 03 The idle AGV is controlled to transport type A material from the type A material storage location to the first production line 1 in the production area I according to the target driving path.

[0066] It can be understood that in the above technical solution, the time optimization model is constructed by taking the minimum time required for the next replenishment of each material as the optimization target, and the time required for the next replenishment of each material is determined according to the material type and scheduling work information. And by taking the ratio between the production progress of multiple required materials within the preset ratio range as the optimization target, the material balance model constructed according to the objective function determines the production progress of each material according to the material type, total demand quantity, time required for the next replenishment and the quantity produced. At the same time, the minimum time required for the automatic replenishment system of the production line to execute the next replenishment and the balance between the production progress of multiple required materials are taken into consideration.

[0067] Finally, according to the time required for the next replenishment of each material and the production progress of each material, the target scheduling plan is determined from the scheduling plans for each material among the multiple required materials and the multiple scheduling plans after the scheduling plans are updated. The target scheduling plan can shorten the production time of the production tasks of the automatic replenishment system of the entire production line while meeting the synchronization of the production progress between various materials in the production goals.

[0068] In some embodiments, Figure 5 As shown, step S160: determining a target scheduling scheme from the scheduling schemes of each material among the multiple required materials and the multiple scheduling schemes after the scheduling schemes are updated according to the time required for the next replenishment of each material and the production progress of each material, including the following steps:

[0069] Step S161: Determine the fitness value corresponding to the scheduling plan for each material based on the time required for the next replenishment of each material and the production progress of each material, and after updating the scheduling plan and the scheduling work information corresponding to the scheduling plan, re-execute the time-based optimization model to determine the time required for the next replenishment of each material based on the material type and the scheduling work information, until the step of updating the scheduling plan and the scheduling work information corresponding to the scheduling plan.

[0070] Specifically, calculating the fitness value corresponding to the scheduling plan can be used as a scoring method for the scheduling plan. The calculation formula for the fitness value corresponding to the scheduling plan for each material is as follows:

[0071]

[0072] in, Indicates the fitness value of the scheduling plan for the specified material. Indicates the time required for the next refill of the specified material. Indicates the time required for the next refill The weight coefficient of Indicates the production progress of the specified material. The weight coefficient that indicates the production progress of the material. and Preset. k represents the kth material.

[0073] In one embodiment, the expression of the time optimization model is as follows:

[0074]

[0075] in, Indicates the time required for the next replenishment of the specified material. The specified material is the material of the scheduling plan. represents the average driving speed of the specified AGV in the scheduling work information, Indicates the distance from the designated AGV to the designated material storage location obtained according to the scheduling work information, Indicates the distance from the designated material storage location to the designated production line of the designated AGV obtained according to the scheduling work information, represents the coefficient of the crossover penalty, represents the number of intersections between the driving path of the specified AGV and the driving paths of other AGVs obtained according to the scheduling work information, Indicates the type of material, and They respectively represent the remaining workload and processing speed of the robot arm in processing the specified material in the scheduling work information, k represents the kth material, i and j are used to indicate the location point on the map, and n and m are used to represent the size of the map.

[0076] Furthermore, the expression of X is as follows:

[0077]

[0078] Among them, X is the path matrix, the path matrix X nm Each represents each location point on the map, i represents the first direction information of the location point, j represents the second direction information of the location point, and the map can be obtained or preset. When it is 1, it means that the location point is the location point where the AGV has traveled. When it is 0, it means that the location point is a location point that the AGV has not traveled to.

[0079] Next, add the matrix X of other AGVs and the matrix X of the specified AGV to get C, where C is the crossover matrix. The expression of the crossover matrix C is as follows:

[0080]

[0081] Among them, each crossover matrix C It also represents each location point on the map, i represents the first direction information of the location point, j represents the second direction information of the location point, when middle The value of is greater than 0, indicating that the location point is the location point where the specified AGV crosses with other AGVs, and The value of is the number of times the specified AGV crosses other AGVs. When the value is 0, it means that the location point is not the location point where the specified AGV crosses other AGVs.

[0082] It can be understood that by inputting the AGV driving information in the scheduling work information into the matrix X and the matrix C, the distance from the specified AGV to the specified material storage location can be obtained. , specify the distance of the AGV from the specified material storage to the specified production line , and the number of intersections between the specified AGV's driving path and other AGV's driving paths .

[0083] It can be understood that, by constructing the path matrix X and the intersection number matrix C, an optimization target of the driving path can be established to obtain a target path with the least driving time.

[0084] In one embodiment, the material balance model is expressed as follows:

[0085]

[0086] in, Indicates the production progress of the specified material. Indicates the quantity of the specified material that has been produced. Indicates the total required quantity of the specified material. Indicates the type of material, Indicates the remaining workload of the robot arm in processing the specified material in the scheduling work information, Indicates the time required for the next refill of the specified material. Indicates the penalty amount for a specified material. It is preset. When the specified material is processed, the penalty amount The value is infinite. When the specified material is not processed, the penalty amount is 0.

[0087] After determining the fitness value corresponding to the scheduling scheme for each material, the scheduling scheme for each material and the scheduling work information corresponding to the scheduling scheme can be updated by selecting different driving routes and / or production lines and other equipment working information to obtain updated scheduling schemes and scheduling work information. Next, the updated scheduling work information is input into the time optimization model and the material balance model, and the fitness value of the updated scheduling scheme is calculated. That is, based on the updated scheduling work information, steps S140, S150, and S161 are re-executed to determine the fitness value corresponding to the scheduling scheme for each material according to the time required for the next replenishment of each material and the production progress of each material, and to update the scheduling scheme and the scheduling work information corresponding to the scheduling scheme.

[0088] In one embodiment, the scheduling scheme for each material is updated according to the octopus algorithm. That is, the updating process of updating the scheduling schemes and the scheduling work information corresponding to the scheduling schemes for the multiple required materials is regarded as the process in which the second tentacle of each of the multiple octopuses performs multiple second selections on the multiple production lines in the equipment work information.

[0089] For example, Figure 3 As shown, the first second choice of the second tentacle of the octopus corresponding to material A is the first production line 1, the second choice is the second production line 2, the third choice is the third production line 3, and the fourth choice is the fourth production line 4. The second to fourth choices are regarded as multiple updates of the scheduling plan for material A.

[0090] Step S162: until the update stop condition is met, multiple groups of scheduling plans corresponding to the multiple required materials are obtained.

[0091] The update stop condition may be that the update times are greater than the times threshold, or that the fitness value of the scheduling scheme is within a preset range. It is understood that each group of scheduling schemes in the multiple groups of scheduling schemes includes a scheduling scheme for each material, and multiple scheduling schemes after the scheduling scheme is updated.

[0092] Step S163: Determine a target scheduling plan according to the scheduling plan for each material and the multiple fitness values ​​corresponding to the multiple scheduling plans after the scheduling plan is updated.

[0093] In one embodiment, according to the scheduling scheme of each material and the multiple fitness values ​​corresponding to the multiple scheduling schemes after the scheduling scheme is updated, the scheduling scheme corresponding to the minimum fitness value among the multiple fitness values ​​is determined as the target scheduling scheme. The time required for the next replenishment of each material and the production progress of each material are respectively in direct proportion to the fitness value.

[0094] For example, the scheduling plan a for material A 01 The fitness value is S1, scheduling scheme a01 Updated multiple scheduling schemes a 02 to a 04 The fitness values ​​are S2, S3 and S4. The scheduling plan for material B 01 The fitness value is S5, scheduling plan b 01 Updated multiple scheduling schemes b 02 To b 04 The fitness values ​​of are S6, S7 and S8. Since the fitness value S3 is the smallest among the fitness values ​​S1 to S8, the scheduling scheme a corresponding to the fitness value S3 is 03 is the target scheduling scheme. It can be understood that at this time, scheduling scheme a 03 The designated AGV is the target AGV, the designated material storage location is the target material storage location, the designated driving path is the target driving path, and the designated production line is the target production line.

[0095] It can be understood that the smaller the fitness value, the shorter the time required for the next refill in the scheduling scheme corresponding to the fitness value, and the slower the production progress of the material. Therefore, after the production line automatic refilling system executes the scheduling scheme, it can complete the transportation of the material with slower production progress in the fastest time.

[0096] In some embodiments, the automatic material replenishment method for a production line based on multi-AGV collaborative handling also includes: when scheduling plans and scheduling work information corresponding to the scheduling plans are updated for multiple required materials respectively, and scheduling execution obstacle information is obtained, the scheduling plan for each material is adjusted according to the scheduling execution obstacle information.

[0097] Scheduling execution obstruction information refers to information that obstructs the automatic material replenishment system of the production line from executing the scheduling plan. For example, the scheduling execution obstruction information includes the storage capacity of the production line being zero and a certain material type being saturated.

[0098] In one embodiment, in combination with the octopus algorithm, the scheduling scheme for each material is adjusted according to the scheduling execution obstruction information. That is, according to the octopus algorithm, the updating process of the scheduling schemes and the scheduling work information corresponding to the scheduling schemes for multiple required materials is regarded as the process of the second tentacle of each octopus in the multiple octopuses making multiple second selections for multiple production lines in the equipment work information. When making multiple second selections, it is simulated that when the second tentacle of each octopus finds the scheduling execution obstruction information, the scheduling execution obstruction information is shared with other octopuses in the multiple octopuses. Other octopuses adjust the second tentacle's next second selection of the production line in the equipment work information according to the scheduling execution obstruction information, and regard the first tentacle's first selection of the unsaturated material and the adjusted second tentacle's next second selection of the production line in the equipment work information as the adjusted scheduling scheme for each material.

[0099] For example, Figure 3 As shown, when the second tentacle of the octopus of material A finds the scheduling execution obstacle information that the storage capacity of the second production line 2 is zero during the second selection, the scheduling execution obstacle information is shared with the octopus of material B. When the octopus of material B makes the next second selection, it avoids the second production line 2 and selects the first production line 1. The first selection of the first tentacle of the octopus of material B for the unsaturated material and the second selection of avoiding the second production line 2 and selecting the first production line 1 are regarded as the adjusted scheduling plan for material B.

[0100] It can be understood that by updating the scheduling plan through multi-tentacle behavior, the "tentacles" of each individual octopus independently search for the best option, and then share and collaborate on information, and share each individual's scheduling plan within the population formed by multiple octopuses, simulating information exchange between octopuses, including some individuals in the population conducting global exploration, while other individuals continue to refine the existing excellent plans to optimize each scheduling plan and determine the optimal target scheduling plan.

[0101] In some embodiments, the method for automatic material replenishment of a production line based on multi-AGV collaborative handling further includes: when there is saturated material and it is determined that the saturated material is placed on the production line of the automatic material replenishment system of the production line, then the idle AGVs among the multiple AGVs are controlled to transport the saturated material back to the warehouse. The saturated material of the multiple required materials is determined according to the total demand quantity, the produced quantity and the material type.

[0102] See also Figure 6 , Figure 6 A schematic structural diagram of a control device for an automatic feeding system of a production line provided in the present application.

[0103] The control device 10 includes a manufacturing execution system module 91 , a path planning module 92 , a robot control system module 93 and an image recognition module 94 .

[0104] The manufacturing execution system module 91 is used to generate material types of multiple required materials and the total required quantity of each of the multiple required materials in response to the production target.

[0105] The robot control system module 93 is used to obtain the equipment working information of the automatic material replenishment system of the production line and the produced quantity of each of the multiple required materials.

[0106] The path planning module 92 is used to obtain a map of the logistics workshop and generate a driving path for the AGV according to the driving information of the AGV in the equipment working information.

[0107] The robot control system module 93 is also used to obtain the material types of multiple required materials generated in response to the production target, and the total required quantity of each material in the multiple required materials; generate a scheduling plan for each material and scheduling work information corresponding to the scheduling plan according to the material type, total required quantity, produced quantity and equipment working information; based on the time optimization model, determine the time required for the next replenishment of each material according to the material type and scheduling work information, and the time optimization model takes the minimum required time for the next replenishment of each material as the optimization target and is constructed according to the objective function; based on the material balance model, determine the time required for the next replenishment of each material according to the material type, total required quantity, next replenishment time, and scheduling work information; The production progress of each material is determined based on the time required for replenishment and the quantity produced. The material balance model takes the ratio between the production progress of multiple required materials within a preset ratio range as the optimization target and is constructed according to the objective function; according to the time required for the next replenishment of each material and the production progress of each material, a target scheduling plan is determined from the scheduling plans of each material among the multiple required materials and multiple scheduling plans after the scheduling plans are updated. The target scheduling plan instructs the idle AGVs in the automatic replenishment system of the production line to transport the target material among the multiple required materials from the target material storage place to the target production line among the multiple production lines according to the target driving path.

[0108] The image recognition module 94 is used to collect the position information of the pallet of the idle AGV, so that the robot control system module 93 controls the idle AGV to correct the placement angle of the pallet according to the position information of the pallet and accurately pick up the target material.

[0109] The image recognition module 94 is also used to obtain the position information of the vertices of the four conveyor line guardrails 32 of the target production line, and determine the posture of the three conveyor lines 31 on the target production line according to the position information of the vertices of the four conveyor line guardrails 32, so that the robot control system module 93 controls the AGV according to the posture of the three conveyor lines 31 to accurately place the required materials on the three conveyor lines 31. In one embodiment, posture recognition can be performed in combination with a neural network model.

[0110] In some embodiments, the robot control system module 93 is also used to determine the fitness value corresponding to the scheduling scheme of each material according to the time required for the next replenishment of each material and the production progress of each material, and after updating the scheduling scheme and the scheduling work information corresponding to the scheduling scheme, re-execute the steps of determining the time required for the next replenishment of each material based on the time optimization model according to the material type and the scheduling work information, and updating the scheduling scheme and the scheduling work information corresponding to the scheduling scheme. Until the update stop condition is met, multiple groups of scheduling schemes corresponding to multiple required materials are obtained, each group of scheduling schemes in the multiple groups of scheduling schemes includes the scheduling scheme of each material, and multiple scheduling schemes after the scheduling scheme is updated; according to the scheduling scheme of each material, and the multiple fitness values ​​corresponding to the multiple scheduling schemes after the scheduling scheme is updated, the target scheduling scheme is determined. According to the scheduling scheme of each material, and the multiple fitness values ​​corresponding to the multiple scheduling schemes after the scheduling scheme is updated, the scheduling scheme corresponding to the minimum fitness value among the multiple fitness values ​​is determined as the target scheduling scheme, wherein the size of the time required for the next replenishment of each material and the production progress of each material are respectively in direct proportion to the fitness value.

[0111] In some embodiments, the robot control system module 93 is also used to adjust the scheduling plan for each material according to the scheduling execution obstacle information when scheduling plans and scheduling work information corresponding to the scheduling plans are updated for multiple required materials respectively and scheduling execution obstacle information is obtained.

[0112] In some embodiments, the robot control system module 93 is also used to determine the unsaturated materials of multiple required materials based on the total demand quantity, the produced quantity and the material type; according to the octopus algorithm, the idle AGV and unsaturated materials in the equipment working information are regarded as the first tentacle and the second tentacle respectively; simulate the first tentacle's first selection of unsaturated materials and the second tentacle's second selection of multiple production lines in the equipment working information to generate multiple octopuses, each of the multiple octopuses representing a scheduling plan for each material.

[0113] In some embodiments, the robot control system module 93 is also used to, according to the octopus algorithm, respectively schedule multiple required materials and update the scheduling work information corresponding to the scheduling schemes, and regard it as a process in which the second tentacle of each of the multiple octopuses makes multiple second selections for multiple production lines in the equipment work information; when making multiple second selections, simulate the second tentacle of each octopus finding scheduling execution obstacle information, and share the scheduling execution obstacle information with other octopuses in the multiple octopuses; other octopuses adjust the second tentacle's next second selection of the production line in the equipment work information according to the scheduling execution obstacle information; regard the first tentacle's first selection of the unsaturated material and the adjusted second tentacle's next second selection of the production line in the equipment work information as the adjusted scheduling scheme for each material.

[0114] In some embodiments, the robot control system module 93 is also used to control the idle AGVs among the multiple AGVs to transport the saturated materials back to the warehouse when there is saturated material and it is determined that the saturated material is placed on the production line of the automatic replenishment system of the production line.

[0115] The robot control system module 93 is used to execute the technical solution provided in any of the aforementioned method embodiments, and its implementation principle and technical effect are similar and will not be repeated here.

[0116] Figure 7 Another structural schematic diagram of the control device provided in this application. Figure 7 As shown, the control device 10 includes:

[0117] Processor 11, memory 12 and bus 13;

[0118] The memory 12 is used to store the computer program code of the processor 11;

[0119] The processor 11 is configured to execute the technical solution of the production line automatic material replenishment method based on multi-AGV collaborative handling in any of the aforementioned method embodiments by executing the computer program code.

[0120] Optionally, the memory 12 may be independent or integrated with the processor 11 .

[0121] The memory 12 is connected to the processor 11 via the bus 13 and completes the communication between them.

[0122] Optionally, the memory 12 may include a random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0123] The bus 13 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0124] The above-mentioned processor can be a general-purpose processor, including a central processing unit CPU, a network processor (NP), etc.; it can also be a digital signal processor DSP, an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0125] The control device 10 is used to execute the technical solution provided in any of the aforementioned method embodiments, and its implementation principle and technical effect are similar and will not be repeated here.

[0126] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A production line automatic material replenishment method based on multi-AGV collaborative handling, applied to the production line automatic material replenishment system, characterized in that: Methods include, In response to the production target, material types of a plurality of required materials and a total required quantity of each of the plurality of required materials are generated; Obtaining equipment working information of the automatic material replenishment system of the production line and the produced quantity of each of the multiple required materials; Generate a scheduling plan for each material and scheduling work information corresponding to the scheduling plan according to the material type, the total demand quantity, the produced quantity and the equipment working information, wherein the scheduling work information refers to the working information of each equipment required to implement the scheduling plan; Based on the time optimization model, the time required for the next refill of each material is determined according to the material type and the scheduling work information. The time optimization model takes the minimum time required for the next refill of each material as the optimization goal and is constructed according to the objective function; Based on the material balance model, the production progress of each material is determined according to the material type, the total required quantity, the time required for the next material replenishment, and the produced quantity. The material balance model is constructed according to the objective function with the ratio between the production progress of multiple required materials within a preset ratio range as the optimization target; According to the time required for the next replenishment of each material and the production progress of each material, a target scheduling scheme is determined from the scheduling schemes for each material among the multiple required materials and the multiple scheduling schemes after the scheduling schemes are updated. The target scheduling scheme instructs idle AGVs among the multiple AGVs in the automatic replenishment system of the production line to transport the target material among the multiple required materials from the target material storage place to the target production line among the multiple production lines according to the target driving path, wherein different driving paths and / or production lines are selected for the scheduling scheme to obtain multiple updated scheduling schemes.

2. The method according to claim 1, characterized in that The step of determining a target scheduling scheme from the scheduling schemes for each material in the plurality of required materials and the plurality of scheduling schemes after the scheduling schemes are updated according to the required time for the next replenishment of each material and the production progress of each material comprises: According to the time required for the next replenishment of each material and the production progress of each material, determine the fitness value corresponding to the scheduling scheme of each material, and after updating the scheduling scheme and the scheduling work information corresponding to the scheduling scheme, re-execute the steps of determining the time required for the next replenishment of each material based on the time optimization model according to the material type and the scheduling work information, and updating the scheduling scheme and the scheduling work information corresponding to the scheduling scheme; Until the update stop condition is met, multiple groups of scheduling plans corresponding to multiple required materials are obtained, each group of scheduling plans in the multiple groups of scheduling plans includes a scheduling plan for each material, and multiple scheduling plans after the scheduling plan is updated; The target scheduling plan is determined according to the scheduling plan for each material and the multiple fitness values ​​corresponding to the multiple scheduling plans after the scheduling plan is updated.

3. The method according to claim 1, characterized in that The expression of the material balance model is as follows: in, Indicates the production progress of the specified material. Indicates the quantity of the specified material that has been produced. Indicates the total required quantity of the specified material. Indicates the type of material, Indicates the remaining workload of the robot arm in processing the specified material in the scheduling work information, Indicates the time required for the next refill of the specified material. Indicates the penalty amount for the specified material.

4. The method according to claim 2, characterized in that: Determining the target scheduling scheme according to the scheduling scheme for each material and the multiple fitness values ​​corresponding to the multiple scheduling schemes after the scheduling scheme is updated includes: According to the scheduling plan for each material and the multiple fitness values ​​corresponding to the multiple scheduling plans after the scheduling plan is updated, the scheduling plan corresponding to the minimum fitness value among the multiple fitness values ​​is determined as the target scheduling plan, wherein the time required for the next replenishment of each material and the production progress of each material are directly proportional to the fitness value.

5. The method according to claim 2, characterized in that: The method further includes, when scheduling schemes and the scheduling work information corresponding to the scheduling schemes are respectively performed on the multiple required materials and scheduling execution obstacle information is acquired, adjusting the scheduling scheme for each material according to the scheduling execution obstacle information.

6. The method according to claim 1, characterized in that The generating of a scheduling plan for each material according to the material type, the total demand quantity, the produced quantity and the equipment working information includes: Determine the unsaturated materials of the multiple required materials according to the total required quantity, the produced quantity and the material types; According to the octopus algorithm, the AGV in the idle state and the unsaturated material in the equipment working information are regarded as the first tentacle and the second tentacle respectively; The first tentacle is simulated to make a first selection of unsaturated materials and the second tentacle is simulated to make a second selection of multiple production lines in the equipment working information, and multiple octopuses are generated, each of which represents a scheduling plan for each material.

7. The method according to claim 5, characterized in that When the scheduling schemes and the scheduling work information corresponding to the scheduling schemes are respectively performed for the multiple required materials and the scheduling execution obstacle information is acquired, the scheduling scheme of each material is adjusted according to the scheduling execution obstacle information, including: According to the octopus algorithm, the updating process of respectively performing scheduling schemes on the multiple required materials and updating the scheduling work information corresponding to the scheduling schemes is regarded as a process in which the second tentacle of each of the multiple octopuses performs multiple second selections on the multiple production lines in the equipment work information; When performing multiple second selections, simulating that when the second tentacle of each octopus finds the scheduling execution obstruction information, the scheduling execution obstruction information is shared with other octopuses in the plurality of octopuses; The other octopus adjusts the second tentacle's next second selection of the production line in the equipment work information according to the scheduling execution obstacle information; The first selection of the unsaturated material by the first tentacle of each octopus in the multiple octopuses and the next second selection of the production line in the equipment working information by the adjusted second tentacle are regarded as the adjusted scheduling plan for each material.

8. The method according to claim 6, characterized in that The method further comprises, When there is saturated material and it is determined that the saturated material is placed on the production line of the automatic replenishment system of the production line, the idle AGVs among the multiple AGVs are controlled to transport the saturated material back to the warehouse.

9. An automatic material replenishment system for a production line, the automatic material replenishment system for the production line comprising a control device, a plurality of AGVs and a plurality of production lines, the control device being used to generate, in response to a production target, a material type of a plurality of required materials and a total required quantity of each of the plurality of required materials; Obtaining equipment working information of the automatic material replenishment system of the production line and the produced quantity of each of the multiple required materials; Generate a scheduling plan for each material and scheduling work information corresponding to the scheduling plan according to the material type, the total demand quantity, the produced quantity and the equipment working information, wherein the scheduling work information refers to the working information of each equipment required to implement the scheduling plan; Based on the time optimization model, the time required for the next refill of each material is determined according to the material type and the scheduling work information. The time optimization model takes the minimum time required for the next refill of each material as the optimization goal and is constructed according to the objective function; Based on the material balance model, the production progress of each material is determined according to the material type, the total required quantity, the time required for the next material replenishment, and the produced quantity. The material balance model is constructed according to the objective function with the ratio between the production progress of multiple required materials within a preset ratio range as the optimization target; According to the time required for the next replenishment of each material and the production progress of each material, a target scheduling scheme is determined from the scheduling schemes of each material among the multiple required materials and multiple scheduling schemes after the scheduling schemes are updated. The target scheduling scheme instructs the idle AGVs among the multiple AGVs in the automatic replenishment system of the production line to transport the target material among the multiple required materials from the target material storage to the target production line among the multiple production lines according to the target driving path, wherein, Different driving routes and / or production lines are selected for the scheduling plan to obtain multiple updated scheduling plans.

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