A material distribution scheduling optimization method, device, medium and equipment

Abstract

The application discloses a kind of material distribution scheduling optimization method, device, medium and equipment.The present application obtains the production shift and beat data of each material, in combination with the preset working parameter (including the standard processing time of different processes and the working efficiency of operator) and the preset maintenance frequency parameter, we simulate the preset scheduling optimization model.This model is based on the production requirements of different processes in production line, material characteristics and the packaging, loading and unloading of material are constructed, the present application can output the distribution quantity and route of each material.Simulation results are used to adjust the distribution plan of each material, to optimize the distribution efficiency and respond to production demand, ensure that material distribution and production rhythm are synchronized, the present application solves the problem that accurate and efficient material scheduling and distribution cannot be carried out in the prior art.

Description

Technical Field

[0001] This invention relates to the field of material distribution scheduling optimization, and more particularly to a material distribution scheduling optimization method, apparatus, medium, and equipment. Background Technology

[0002] With the rapid development of automation and intelligence, AGVs are widely used in manufacturing, especially in material transportation and production scenarios. Currently, many large manufacturing plants have chosen to use AGVs. AGV is an intelligent mobile robot, mainly used as a transportation tool. It is small and flexible, has a large carrying capacity, and adjustable carrying form. It can cooperate in handling materials and realize lifting, lowering, and rotating. It can also be made into various forms such as towing type and detached type, and has many advantages. Moreover, it is easy to control.

[0003] The transportation and distribution of materials is not complicated. The large-scale use of AGVs in material distribution can reduce the labor costs of hiring dedicated material delivery personnel.

[0004] Currently, the material distribution needs of a production line are inconsistent, mainly due to the characteristics of the materials, the features of the products, and the production needs of the production line. Therefore, to simplify material distribution, material requirements are generally configured separately according to the different processes of different production lines, and material distribution routes and trolleys are planned separately. If there are multiple processes for distribution logistics needs, multiple production lines will be configured, resulting in an imbalance in resource allocation. The most direct impact is on space allocation, with most of the factory space used for production line layout, leaving very little space specifically planned for material distribution. Secondly, multiple distribution routes can lead to intersections and overlaps, increasing the number of avoidance rules, increasing the difficulty of distribution, and hindering transportation efficiency. These factors prevent existing technologies from accurately and efficiently scheduling and distributing materials. Summary of the Invention

[0005] This invention provides a method, apparatus, medium, and equipment for optimizing material distribution scheduling, in order to solve the problem that the prior art cannot perform accurate and efficient material distribution scheduling.

[0006] Firstly, this application provides a method for optimizing the scheduling of material distribution, including:

[0007] Obtain production shift and cycle time data for each material;

[0008] Based on the production shifts, cycle time data, preset working parameters, and preset maintenance frequency parameters, the preset scheduling optimization model is simulated so that the scheduling optimization model outputs the delivery quantity and route of each material.

[0009] The preset scheduling optimization model is constructed according to production requirement data of different processes in the production line, material characteristic data, and packaging, loading and unloading of each material.

[0010] According to the distribution quantity and route of each material, the distribution plan of each material is adjusted.

[0011] The application adjusts the distribution plan of each material according to the distribution quantity and route of each material.

[0012] As a preferred embodiment of the first aspect, the preset scheduling optimization model is constructed according to production requirement data of different processes in the production line, material characteristic data, and packaging, loading and unloading of each material, specifically:

[0013] The production requirements of different processes, the material characteristics of different processes, the packaging method of each material, the loading method of each material and the unloading method of each material are obtained.

[0014] The production requirements include production capacity, production rhythm, workstation layout and staff configuration of different processes; the material characteristics include size, weight, shape and quantity of each material; the packaging method includes size, weight limit and stacking requirement of packaging; the loading method of each material includes using a forklift, automatically drilling into the bottom of a rack and unhooking loading; and the unloading method includes waiting for staff to unload at a preset workstation control point or a trolley entering a workstation to complete assembly and processing work with workers.

[0015] According to the production requirements and material characteristics, an initial scheduling optimization model is constructed.

[0016] According to the packaging method, the loading method, the unloading method and the initial scheduling optimization model, a preset scheduling optimization model is constructed.

[0017] In this preferred embodiment, the present application builds a preset scheduling optimization model by comprehensively considering the production requirements of different processes in the production line, the characteristics of the materials, and the packaging, loading, and unloading of the materials. This method can accurately match the specific needs of each process and the characteristics of the materials. The analysis of production requirements ensures that the model can adapt to the production capacity, tempo, layout, and staff configuration of different processes, while the consideration of material characteristics ensures that the model can handle the size, weight, shape, and quantity of different materials. Detailed analysis of packaging methods, loading methods, and unloading methods further optimizes the material handling and storage process. Therefore, the beneficial effects of this comprehensive method are to improve the accuracy and efficiency of material distribution, reduce bottlenecks and waste in production, and ultimately improve overall production efficiency and reduce costs. Through this fine scheduling optimization, the production line can better respond to changes, improve production flexibility and adaptability, and ultimately achieve more efficient production operations.

[0018] As a preferred embodiment of the first aspect, the preset scheduling optimization model is constructed according to the packaging method, loading method, unloading method, and initial scheduling optimization model, specifically:

[0019] According to the packaging method, including the size, weight limit, and stacking requirements of the packaging, the impact of material loading and unloading on efficiency is evaluated;

[0020] According to the loading method of each material, including the use of a forklift, automatic drilling into the bottom of the rack, and unhooked loading, the impact of each technology on loading time is evaluated;

[0021] According to the impact of material loading and unloading on efficiency, the impact of each technology on loading time, and the unloading method, a preset scheduling optimization model is constructed.

[0022] By analyzing the packaging method of the material in detail, including the size, weight limit, and stacking requirements, the present application can evaluate the specific impact of material loading and unloading on efficiency, thereby identifying possible bottlenecks and optimization points. Further, considering different loading techniques, such as the use of a forklift, automatic drilling into the bottom of the rack, and unhooked loading, the present application evaluates the specific impact of these techniques on loading time, which helps to optimize the efficiency of loading operations. Combining these analysis results, as well as the unloading method of the material, the present application constructs a preset scheduling optimization model. This model can accurately predict and plan the key time nodes and operation steps in the material distribution process, thereby reducing waiting and processing time and improving overall material distribution efficiency. Therefore, the beneficial effects of this method are to reduce non-value-added time in production by accurately controlling and optimizing the loading, transportation, and unloading processes of materials, improve the operation efficiency of the production line, and ultimately achieve cost savings and production capacity improvement.

[0023] As a preferred embodiment of the first aspect, the preset scheduling optimization model is constructed according to the loading and unloading efficiency of the material, the influence of the various technologies on the loading time, and the unloading mode, specifically:

[0024] According to the loading and unloading efficiency of the material, the influence of the various technologies on the loading time, and the unloading mode, a transportation route planning model for each material is constructed;

[0025] According to the preset parameters, control points for information feedback and task scheduling of the scheduling system are set up on the preset key path of the transportation route, to obtain a control point model;

[0026] According to the control point model and the transportation route, a preset scheduling optimization model is constructed.

[0027] In this preferred embodiment, the present application can construct an accurate transportation route planning model by comprehensively considering the loading and unloading efficiency of the material, the influence of different loading technologies on the loading time, and the specific unloading mode. This model can set up control points on the key path of the transportation route according to preset parameters, and these control points are used for information feedback and task scheduling of the scheduling system, thereby forming a control point model. In combination with the control point model and the transportation route, the present application finally constructs a preset scheduling optimization model. The beneficial effect of this model is that it can ensure that each link in the material distribution process is accurately controlled and optimized, thereby reducing delays and bottlenecks in distribution and improving overall logistics efficiency. In this way, the production line can more flexibly respond to changes in production demand, reduce material waiting and handling time, reduce logistics costs, improve the throughput and response speed of the production line, and ultimately achieve significant improvement in production efficiency and optimal allocation of resources.

[0028] As a preferred embodiment of the first aspect, the preset scheduling optimization model is simulated according to the production shift, the beat data, the preset working parameter, and the preset maintenance frequency parameter, so that the scheduling optimization model outputs the distribution quantity and route of each material, specifically:

[0029] According to the production shift, the total working time and rest time within a day or a shift are determined;

[0030] According to the total working time and rest time, the effective time actually available for production is calculated;

[0031] According to the beat data, the production rate satisfying the preset demand is calculated;

[0032] simulate the dispatch optimization model according to the effective time, the production rate, preset working parameters and preset maintenance frequency parameters, so that the dispatch optimization model outputs the dispatch quantity and route of each material after simulating the material dispatch process under different production conditions;

[0033] The preset working parameters include standard processing time of different processes and preset operator working efficiency;

[0034] The preset maintenance frequency parameters include periodic maintenance and repair time of preset equipment and preset mobile robots.

[0035] In this preferred embodiment, the effective time actually available for production can be calculated by determining the total working time and rest time in a day or a shift according to the production shift. Combined with the tact data, i.e. the ideal production interval time of each product, the production rate meeting the preset demand can be calculated. Using these effective time and production rate, together with preset working parameters and maintenance frequency parameters, the dispatch optimization model is simulated. Such simulation can simulate the material dispatch process under different production conditions, and output the dispatch quantity and route of each material. The simulation method of the present application can ensure that the material dispatch plan is synchronized with the actual production demand, reduce waiting and delay in the dispatch process, and improve the material flow efficiency. Further, adjusting the material dispatch plan according to the simulation result can optimize the dispatch path, reduce unnecessary transportation, reduce cost, and improve the overall production efficiency and flexibility in responding to market changes.

[0036] In a second aspect, the present application provides a dispatch optimization device for material dispatch. The dispatch optimization device for material dispatch includes an acquisition module, a simulation module and an optimization module;

[0037] The acquisition module is used to acquire the production shift and tact data of each material;

[0038] The simulation module is used to simulate the dispatch optimization model according to the production shift, tact data, preset working parameters and preset maintenance frequency parameters, so that the dispatch optimization model outputs the dispatch quantity and route of each material;

[0039] The preset dispatch optimization model is constructed according to production requirement data of different processes in the production line, material characteristic data and packaging, loading and unloading conditions of each material;

[0040] The optimization module is used to adjust the dispatch plan of each material according to the dispatch quantity and route of each material.

[0041] The device uses three modules to work together and coordinate to better schedule the distribution of materials. The application obtains the production shift and beat data of each material, and combines the preset working parameters and maintenance frequency parameters to simulate the preset scheduling optimization model. The model considers the production requirements of different processes in the production line, the characteristics of the materials, and the packaging, loading, and unloading of the materials, so as to output accurate material distribution quantity and route. This comprehensive simulation method can ensure that the material distribution plan is synchronized with the actual production demand, reduce waiting and delay in the distribution process, and improve the efficiency of material flow. Further, adjusting the material distribution plan according to the simulation results can optimize the distribution path, reduce unnecessary transportation, reduce costs, and improve overall production efficiency and flexibility in responding to market changes. Therefore, the application can realize more efficient and accurate material distribution, enhance the coordination of the production line, and solve the problem of inaccurate and inefficient material scheduling and distribution in the prior art.

[0042] In a third aspect, the application provides a computer-readable storage medium comprising a stored computer program, wherein the computer program, when executed, controls a device in which the computer-readable storage medium is located to perform the material distribution scheduling optimization method as described. The beneficial effects are the same as those of the material distribution scheduling optimization method provided in the first aspect of the application.

[0043] In a fourth aspect, the application provides a terminal device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements any one of the material distribution scheduling optimization methods according to the first aspect when executing the computer program. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 FIG. 1 is a flowchart of an embodiment of the material distribution scheduling optimization method provided by the application;

[0045] Figure 2 FIG. 2 is a structural diagram of an embodiment of each process of the production line provided by the application;

[0046] Figure 3 FIG. 3 is a structural diagram of an embodiment of the characteristics and relationships of the processes and materials provided by the application;

[0047] Figure 4 FIG. 4 is a structural diagram of an embodiment of the preliminary loading and unloading model provided by the application;

[0048] Figure 5 FIG. 5 is a structural diagram of an embodiment of the material distribution scheduling optimization device provided by the application. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of the present application.

[0050] Embodiment one

[0051] Please refer to Figure 1 A scheduling optimization method for material distribution is provided in the embodiments of the present application.

[0052] In the embodiments, the process of the scheduling optimization method for material distribution in the present application is described in detail through steps S01-S03.

[0053] S01: Obtain the production shift and beat data of each material.

[0054] S02: According to the production shift, beat data, preset working parameter and preset maintenance frequency parameter, simulate the preset scheduling optimization model, so that the scheduling optimization model outputs the distribution quantity and route of each material.

[0055] The preset scheduling optimization model is constructed according to the production requirement data of different processes in the production line, the material characteristic data and the packaging, loading and unloading conditions of each material.

[0056] As a preferred embodiment of embodiment one, the preset scheduling optimization model is constructed according to the production requirement data of different processes in the production line, the material characteristic data and the packaging, loading and unloading conditions of each material, specifically:

[0057] 1. Obtain the production requirements of different processes in the production line.

[0058] (1) Confirm the layout of the current production line: the layout type of the current production line is one-dimensional, and the production line is produced in a flow line manner.

[0059] (2) The current one-dimensional processing production line has 6 processes, each process corresponds to one type of material (the weight and size of each type of material are consistent), the number of stations of different processes is inconsistent, and the number of configured production employees is also inconsistent, as shown in Figure 2

[0060] 2. Obtain the material characteristics of different processes.

[0061] (1) The material characteristics of different processes are different, mainly classified from shape, weight and size, according to the characteristics of 6 processes, the characteristics and relationship of processes and materials are sorted, as shown in​Figure 3 as shown;

[0062] The material types of this production line are roughly divided into four types, all of which are parts packed in boxes, including nut and screw parts, wire harness parts, and large assembly parts. The last process 6 is quality inspection, which is mainly performed by operators using quality inspection tools. Process 6 (station 11) does not require the distribution of parts;

[0063] 3. Obtain the material packaging, loading and unloading conditions:

[0064] ①Material packaging method: according to the size of the material combined with the weight to match the corresponding material rack and material box;

[0065] ②There are three ways to load materials onto the trolley, one is forklift loading, i.e. backpack loading; the trolley automatically drills to the bottom of the rack, cooperates with the lifting structure, and drags the rack to run; there is also unhooked loading, the trolley is aligned with the unhooked, and the rack is pulled forward;

[0066] ③There are two ways for the trolley to unload materials to the station, one is to go to the station control point, wait for the worker to unload the materials, and the trolley returns empty with the rack, the second is for the trolley to enter the station and cooperate with the worker to complete the assembly and processing work of the station and then return empty with the rack;

[0067] Further, according to the collected relevant materials for simulation, the simulation process is as follows:

[0068] (1) Establish a production line model:

[0069] ①Establish a station model: establish a three-dimensional entity model for simulation, establish a processor model to represent each station, and adjust the average processing time of each station to represent the production time of the station;

[0070] ②Establish a station operator model: establish a three-dimensional entity model for simulation, establish a human body model, and the work content of each employee is to assist the processor to complete the processing task, and establish a matching model of the employee and the station;

[0071] ③Establish a path model: establish a path model to guide the transportation route of the trolley, which can be one-way or two-way, and the path can set the maximum number of AGVs allowed to pass through the current road. In order to improve production efficiency, on the one hand, avoid the problem of frequent opposite route avoidance, the entire route is designed as a large loop type route, and on the other hand, multiple branches are set at the unavoidable opposite routes, and the trolley can choose to wait in the branch path;

[0072] ④Establish a control point model: add a control point on the path to represent the current point, set up a control point on the key path, and then write parameters on the control point, which can realize the information feedback of AGV and the dispatching system;

[0073] (2) Simulate materials and racks:

[0074] ① Simulate material generation: By establishing a material generator, according to the schedule of the material, set the size and quantity of the material, the material generator will generate different materials according to the set parameters, in order to distinguish, you can set different colors for different materials, and give each material a model, which represents the material type;

[0075] ② Simulate rack generation: By establishing a rack generator, in order to distinguish, set different appearance parameters of the rack, and in order to match the material, set the color and model of the rack consistent with the material;

[0076] ③ Combination: By establishing a processing processor, when each material reaches a certain quantity matching a rack, combine the material with the rack;

[0077] (3) Simulate the loading and unloading model of the trolley:

[0078] ① Establish AGV simulation model: The simulation system has a set AGV model, which can adjust speed, acceleration, size and power consumption, etc. The initialization sets the number of trolleys to the maximum number that the layout can accommodate, and sets a number for each trolley. The trolley can stop at the control point of the path, and the dispatching system can get the trolley number corresponding to the control point;

[0079] ② Dispatching system model: Establish a three-dimensional entity simulation model and a computer / upper computer dispatching system;

[0080] ③ Call material process model: Establish a call material model. This process is mainly a way of information transmission, without a three-dimensional entity model. A custom logic tool is established in the simulation model tool interface, initialized and set, and an information transmission parameter is established for each station to interact with the dispatching system. When the material of the current station can maintain the production line for 30 minutes or less, start sending a call task to the dispatching system. The priority of normal task arrangement is according to the order. If calling at the same time, the dispatching system will adjust the priority of the task after receiving the task. The priority of arranging the material distribution task is: process 1> process 2> process 3> process 4> process 5> process 6;

[0081] ④ Execute the loading process: This model can execute the material task of 3 processes at a time, according to the call task arrangement, dispatch 3 trolleys to 3 processes at a time to execute the loading task. The trolley arrives at the loading control point. In order to distinguish, simplify the use of forklift, automatic recognition of unhooking and automatic drilling to the bottom of the rack, which are several loading animations. The difference between loading methods is that the loading time is different, so this case is distinguished by loading time;

[0082] ⑤ Execute the simulation of unloading: the trolley arrives at the unloading station, and executes the unloading requirement according to the requirements of different stations;

[0083] A preliminary unloading model is established as shown in Figure 4 .

[0084] (4) Process flow of model establishment:

[0085] The process flow of the simulation model is used to connect the path, three-dimensional entity model, scheduling system and related parameters established by simulation according to the entire production flow, so as to establish a logical system conforming to a complete production flow.

[0086] In this preferred embodiment, the preset scheduling optimization model is constructed by comprehensively considering the production requirements of different processes in the production line, the characteristics of the materials, and the packaging, loading and unloading of the materials. This method can accurately match the specific requirements of each process and the characteristics of the materials. The analysis of production requirements ensures that the model can adapt to the production capacity, tempo, layout and staff configuration of different processes, while the consideration of material characteristics ensures that the model can handle the size, weight, shape and quantity of different materials. Detailed analysis of the packaging method, loading method and unloading method further optimizes the material handling and storage process. Therefore, the beneficial effects of this comprehensive method are to improve the accuracy and efficiency of material distribution, reduce bottlenecks and waste in production, and thus improve the overall production efficiency and reduce costs. Through this fine scheduling optimization, the production line can better respond to changes, improve the flexibility and adaptability of production, and ultimately achieve more efficient production operations.

[0087] As a preferred embodiment of embodiment one, the preset scheduling optimization model is simulated according to the production shift, tempo data, preset working parameters and preset maintenance frequency parameters, so that the scheduling optimization model outputs the distribution quantity and route of each material, specifically:

[0088] The EXCEL shift and tempo are imported into the simulation model interface, and the average line efficiency under a single shift and the production efficiency of each process and station are obtained;

[0089] The processors of all stations are set with working and maintenance frequency, maintenance time and other related parameters in the attribute interface;

[0090] The number of control points of the model is balanced. The control point is the exploration point of the trolley executing the task forward, and is also the carrier of the signal interaction between the trolley and the scheduling system. According to the size of the trolley and the space layout, combined with the actual navigation mode of the trolley, the number of control points in the model is reasonably set.

[0091] The simulation is ended, and the line efficiency, the production efficiency of each station, and the average loading time of the trolley are exported. The production efficiency is compared with the historical production efficiency of the line to determine whether it meets the normal production requirements of the line.

[0092] In this preferred embodiment, the application determines the total working time and rest time within a day or a shift based on the production shift, and calculates the effective time available for production. Combined with the tact data, i.e. the ideal production interval time of each product, the application can calculate the production rate that meets the preset demand. Using these effective time and production rate, together with the preset working parameters and maintenance frequency parameters, the preset scheduling optimization model is simulated. Such simulation can simulate the material distribution process under different production conditions and output the distribution quantity and route of each material. The simulation method of the application can ensure that the material distribution plan is synchronized with the actual production demand, reduce waiting and delay in the distribution process, and improve the material flow efficiency. Further, adjusting the material distribution plan according to the simulation results can optimize the distribution path, reduce unnecessary transportation, reduce costs, and improve the overall production efficiency and flexibility in responding to market changes.

[0093] S03: Adjust the distribution plan of each material according to the distribution quantity and route of each material.

[0094] As a preferred embodiment of embodiment one, the adjustment of the distribution plan of each material according to the distribution quantity and route of each material is specifically:

[0095] According to the simulation results, the number of trolleys required to meet the material demand under the condition of meeting the production efficiency of the line at different tacts is determined as the lower limit value.

[0096] If the tact is constant and the line efficiency is met, the lower limit value of the call of different stations is changed, and the number of trolleys required is determined as the lower limit value.

[0097] If the line efficiency is met and the lower limit value of the call of different stations is unchanged, the production tact is improved, and the number of trolleys required is determined as the lower limit value.

[0098] The application obtains production shift and rhythm data of each material, and simulates a preset scheduling optimization model in combination with preset working parameters and maintenance frequency parameters. The model comprehensively considers production requirements of different processes in the production line, material characteristics, and material packaging, loading, and unloading conditions, so as to output accurate material distribution quantity and route. This comprehensive simulation method can ensure that the material distribution plan is synchronized with the actual production demand, reduce waiting and delay in the distribution process, and improve material flow efficiency. Further, adjusting the material distribution plan according to the simulation result can optimize the distribution path, reduce unnecessary transportation, reduce cost, and improve overall production efficiency and flexibility in responding to market changes. Therefore, the application can realize more efficient and accurate material distribution, enhance the coordination of the production line, and solve the problem of inaccurate and inefficient material scheduling and distribution in the prior art.

[0099] Embodiment Two

[0100] Please refer to Figure 5 A material distribution scheduling optimization device is provided for the embodiments of the application.

[0101] In this embodiment, the material distribution scheduling optimization device comprises an acquisition module 10, a simulation module 20, and an optimization module 30.

[0102] The acquisition module 10 is configured to acquire production shift and rhythm data of each material.

[0103] The simulation module 20 is configured to simulate a preset scheduling optimization model according to the production shift, rhythm data, preset working parameters, and preset maintenance frequency parameters, so that the scheduling optimization model outputs the distribution quantity and route of each material.

[0104] The preset scheduling optimization model is constructed according to production requirement data of different processes in the production line, material characteristic data, and packaging, loading, and unloading conditions of each material.

[0105] As a preferred embodiment of Embodiment Two, the preset scheduling optimization model is constructed according to production requirement data of different processes in the production line, material characteristic data, and packaging, loading, and unloading conditions of each material, specifically as follows:

[0106] 1. Obtain production requirements of different processes in the production line.

[0107] (1) Confirm the layout of the current production line: the layout type of the current production line is linear, and the production line is produced in a flow line manner.

[0108] (2) Current one-word processing line has 6 processes, each process corresponds to a class of materials (the weight, size and quantity of each class of materials are consistent), the number of stations in different processes is inconsistent, and the number of production employees configured is also different, as shown in Figure 2 ;

[0109] 2. Obtain the characteristics of materials in different processes:

[0110] (1) The characteristics of materials in different processes are different, mainly classified by shape, weight and size. According to the characteristics of the 6 processes, the characteristics and relationship between the processes and the materials are sorted out, as shown in Figure 3 ;

[0111] The material types of this line are roughly divided into 4 types, all of which are parts packed in boxes, including nut and screw parts, wire harness parts, and large assembly parts. The last process 6 is quality inspection, mainly performed by operators using quality inspection tools. Process 6 (station 11) does not need to distribute parts;

[0112] 3. Obtain the material packaging, loading and unloading conditions:

[0113] ① Material packaging method: according to the size of the material combined with the weight to match the corresponding material rack and material box;

[0114] ② There are 3 ways to load materials onto the trolley, one is forklift loading, i.e. backpack loading; the trolley automatically drills to the bottom of the rack, cooperates with the lifting structure, and drags the rack to run; there is also unhooked loading, the trolley aligns with the unhooked, and pulls the rack forward;

[0115] ③ There are 2 ways for the trolley to unload materials to the station, one is to go to the station control point, wait for the worker to unload the materials, and the trolley returns empty with the rack; the other is for the trolley to enter the station and cooperate with the worker to complete the assembly and processing work in the station and then return empty with the rack;

[0116] Further, according to the collected relevant materials, simulation is carried out, and the simulation process is as follows:

[0117] (1) Establish the line model:

[0118] ① Establish the station model: establish a three-dimensional entity model for simulation, establish a processor model to represent each station, and adjust the average processing time of each station to represent the production time of the station;

[0119] ② Establish the station operator model: establish a three-dimensional entity model for simulation, establish a human body model, and the work content of each employee is to assist the processor to complete the processing task, and establish a matching model of employees and stations;

[0120] ③Establish path model: Establish path model, path guide car transportation route, one-way, two-way, path can set the current road maximum allowed AGV number; In order to improve production efficiency, on the one hand to avoid frequent opposite route avoidance problem, the whole route is designed into a large ring type route, on the other hand, in the unavoidable opposite road set multiple branches, car can choose in branch waiting;

[0121] ④Establish control point model: Add control points, establish on the path, indicate the current point, set up control points on the key path, and then write parameters on the control points, which can realize the information feedback of AGV and scheduling system;

[0122] (2) Simulate material and rack:

[0123] ①Simulate material generation: By establishing material generator, according to the time table of material arrival, set the size and quantity of material, material generator will generate different materials according to the set parameters, in order to distinguish, can set different color parameters for different materials, at the same time, give each kind of material a model, represent material type;

[0124] ②Simulate rack generation: By establishing rack generator, in order to distinguish, set different appearance parameters of rack, at the same time, in order to match the material, set the color and model of rack consistent with the material;

[0125] ③Combination: By establishing a processing processor, when each kind of material reaches a certain quantity matching a rack, combine the material with the rack;

[0126] (3) Simulate car loading and unloading model:

[0127] ①Establish AGV simulation model: The simulation system has set AGV model, which can adjust speed, acceleration, size and power consumption, etc. The initialization setting car number is the maximum upper limit number that can be accommodated by layout, set the number for each car. The car can stop at the control point of the path, and the scheduling system can get the car number corresponding to the control point;

[0128] ②Scheduling system model: Establish three-dimensional entity simulation model, establish computer / scheduling system of host computer;

[0129] ③Calling process model: a calling model is established, this process is mainly the way of information transmission, there is no three-dimensional entity model, a custom logic tool is established in the simulation model tool interface, initialization setting is performed, an information transmission parameter for interacting with the scheduling system is established for each station, when the material of the current station can maintain the production line to continue for 30 min or less, the calling task is started to be sent to the scheduling system, the priority of the normal arrangement task is according to the order, if calling at the same time, the scheduling system receives the task, the priority of the task is adjusted, the priority of the arrangement distribution material task is: process 1> process 2> process 3> process 4> process 5> process 6;

[0130] ④Execution of the feeding process: the model can execute the material task of 3 processes at a time, according to the calling task arrangement, 3 trolleys are dispatched to 3 feeding points of the processes to execute the feeding task; the trolley arrives at the feeding control point, in order to distinguish and simplify, the animations of the forklift, automatic identification of unhooking and automatic drilling to the bottom of the rack are used, the difference of the loading mode is that the loading time is inconsistent, therefore, the loading time is used to distinguish the difference of the loading mode in the case;

[0131] ⑤Execution of the unloading simulation: the trolley arrives at the unloading station, and the unloading demand is executed according to the requirements of different stations;

[0132] A preliminary feeding and unloading model is established as shown in Figure 4

[0133] (4) Process flow of the established model

[0134] The process flow of the simulation model is established, which is used to connect the path, three-dimensional entity model, scheduling system and related parameters according to the whole production flow, and establish a logical system conforming to a complete production flow.

[0135] In the preferred embodiment, the preset scheduling optimization model is constructed by comprehensively considering the production requirements of different processes in the production line, the characteristics of the materials, and the packaging, loading and unloading of the materials. This method can accurately match the specific needs of each process and the characteristics of the materials. The analysis of production requirements ensures that the model can adapt to the production capacity, tempo, layout and staff configuration of different processes, while the consideration of the characteristics of the materials ensures that the model can handle the size, weight, shape and quantity of different materials. Detailed analysis of the packaging mode, loading mode and unloading mode further optimizes the material handling and storage process. Therefore, the beneficial effects of this comprehensive method are to improve the accuracy and efficiency of material distribution, reduce bottlenecks and waste in production, and ultimately improve the overall production efficiency and reduce costs. Through this fine scheduling optimization, the production line can better respond to changes, improve the flexibility and adaptability of production, and ultimately achieve more efficient production operations.

[0136] ​As a preferred embodiment of embodiment two, the preset scheduling optimization model is simulated according to the production shift, the beat data, the preset work parameter and the preset maintenance frequency parameter, so that the scheduling optimization model outputs the distribution quantity and route of each material, specifically:

[0137] In the simulation model interface, the EXCEL shift and beat are imported to obtain the average production line efficiency under a single shift and the production efficiency of each process and station;

[0138] The processors of all stations are set with the frequency of work and maintenance, the maintenance time and other related parameters in the attribute interface;

[0139] The number of control points of the balance model is controlled. The control points are exploration points of the trolley to the forward task and are carriers of signal interaction between the trolley and the scheduling system. According to the size of the trolley and the space layout, the number of control points in the model is reasonably set in combination with the actual navigation mode of the trolley.

[0140] After the simulation is run, the production line efficiency, the production efficiency of each station, the average loading time of the trolley and the like are exported. Whether the production efficiency meets the normal production line demand is compared with the historical production efficiency.

[0141] In this preferred embodiment, the total work time and rest time in a day or a shift are determined according to the production shift, so that the effective time actually available for production can be calculated. In combination with the beat data, i.e. the ideal production interval time of each product, the production rate meeting the preset demand can be calculated. By using these effective time and production rate, together with the preset work parameter and maintenance frequency parameter, the preset scheduling optimization model is simulated. Such simulation can simulate the material distribution process under different production conditions and output the distribution quantity and route of each material. The simulation method of the present application can ensure that the material distribution plan is synchronized with the actual production demand, reduce the waiting and delay in the distribution process, improve the material turnover efficiency. Further, according to the simulation result, the material distribution plan is adjusted, which can optimize the distribution path, reduce unnecessary transportation, reduce the cost, and improve the overall production efficiency and the flexibility of responding to market changes.

[0142] The optimization module 30 is used for adjusting the distribution plan of each material according to the distribution quantity and route of each material.

[0143] As a preferred embodiment of embodiment two, the distribution plan of each material is adjusted according to the distribution quantity and route of each material, specifically:

[0144] According to the simulation result, the lower limit value of the number of distribution trolleys required to meet the material demand under the demand of the production efficiency of the production line under different beats is required;

[0145] If the beat is constant, meet the line efficiency, the lower limit value of different station call material changes, the number of distribution trolley lower limit value;

[0146] If the beat is constant, meet the line efficiency, the lower limit value of different station call material changes, the number of distribution trolley lower limit value.

[0147] The device uses three modules to work better to dispatch the material distribution, the application obtains the production shift and beat data of each material, and combines the preset working parameters and maintenance frequency parameters to simulate the preset scheduling optimization model, the model considers the production requirements of different processes in the production line, the characteristics of the material and the packaging, loading and unloading of the material, so as to output accurate material distribution quantity and route. This comprehensive simulation method can ensure that the material distribution plan is synchronized with the actual production demand, reduce the waiting and delay in the distribution process, and improve the material flow efficiency. Further, according to the simulation result, the material distribution plan is adjusted, the distribution path is optimized, unnecessary transportation is reduced, the cost is reduced, and the overall production efficiency and the flexibility of responding to market changes are improved. Therefore, the application can realize more efficient and accurate material distribution, enhance the coordination of the production line, and solve the problem of accurate and efficient material scheduling and distribution in the prior art.

[0148] Example three:

[0149] The embodiment of the application provides a computer readable storage medium, the computer readable storage medium comprises a stored computer program, wherein when the computer program runs, the device where the computer readable storage medium is located executes the material distribution scheduling optimization method;

[0150] If the scheduling optimization method for material distribution is implemented in the form of a software functional unit and used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer-readable medium can include any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0151] Embodiment Four

[0152] The present application provides a terminal device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements any one of the scheduling optimization methods for material distribution as described in Embodiment One when executing the computer program.

[0153] The above-described specific embodiments further illustrate the purposes, technical solutions, and beneficial effects of the present application. It should be understood that the above-described specific embodiments are merely examples of the present application and are not intended to limit the protection scope of the present application. It is particularly pointed out that any modifications, equivalent replacements, improvements, etc. made by those skilled in the art within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for scheduling optimization of material distribution, characterized in that, The method comprises the following steps: Obtain production shift and tact data of each material; Simulate a preset scheduling optimization model according to the production shift, tact data, preset working parameters and preset maintenance frequency parameters, so that the scheduling optimization model outputs the distribution quantity and route of each material; specifically: Determine the total working time and rest time within a day or a shift according to the production shift; Calculate the effective time available for production according to the total working time and rest time; Calculate the production rate that meets the preset demand according to the tact data; Simulate a preset scheduling optimization model according to the effective time, production rate, preset working parameters and preset maintenance frequency parameters, so that the scheduling optimization model outputs the distribution quantity and route of each material after simulating the material distribution process under different production conditions; The preset scheduling optimization model is constructed according to production requirement data of different processes in the production line, material characteristic data, and packaging, loading and unloading of each material, specifically: Obtain production requirements of different processes, material characteristics of different processes, packaging methods of each material, loading methods of each material and unloading methods of each material; The production requirements include production capacity, production tact, workstation layout and employee allocation of different processes; the material characteristics include size, weight, shape and quantity of each material; the packaging method includes size, weight limit and stacking requirement of packaging; the loading method of each material includes using a forklift, automatically drilling into the bottom of a rack and unhooking loading; the unloading method includes waiting for an employee to unload at a preset workstation control point or a trolley entering a workstation to complete assembly and processing work with a worker; Construct an initial scheduling optimization model according to the production requirements and material characteristics; Construct a preset scheduling optimization model according to the packaging method, loading method, unloading method and initial scheduling optimization model; Adjust the distribution plan of each material according to the distribution quantity and route of each material.

2. The method of scheduling optimization for material distribution of claim 1, wherein, The preset scheduling optimization model is constructed according to the packaging method, loading method, unloading method and initial scheduling optimization model, specifically: According to the packaging method including size, weight limit and stacking requirement of packaging, the influence of material loading and unloading on efficiency is evaluated; According to the loading method of each material including using a forklift, automatically drilling into the bottom of a rack and unhooking loading, the influence of each technology on loading time is evaluated; According to the influence of material loading and unloading on efficiency, the influence of each technology on loading time and the unloading method, a preset scheduling optimization model is constructed.

3. The method of scheduling optimization for material distribution of claim 2, wherein, The preset scheduling optimization model is constructed according to the influence of material loading and unloading on efficiency, the influence of each technology on loading time and the unloading method, specifically: According to the influence of the loading and unloading of the materials on the efficiency, the influence of the various technologies on the loading time, and the unloading mode, a transportation route for each material is planned; According to the preset parameters, a control point for scheduling system information feedback and task scheduling is set up on a preset key path of the transportation route, and a control point model is obtained; According to the control point model and the transportation route, a preset scheduling optimization model is constructed.

4. The method of scheduling optimization for material distribution of claim 1, wherein, The preset working parameters include standard processing time of different processes and working efficiency of preset operators.

5. The method of scheduling optimization for material distribution of claim 1, wherein, The preset maintenance frequency parameters include periodic maintenance and repair time of preset equipment and preset mobile robots.

6. A dispatch optimization apparatus for material distribution, characterized by, The simulation module is used to simulate the preset scheduling optimization model according to the production shift, the beat data, the preset working parameters, and the preset maintenance frequency parameters, so that the scheduling optimization model outputs the distribution quantity and the route of each material; and the simulation of the preset scheduling optimization model according to the production shift, the beat data, the preset working parameters, and the preset maintenance frequency parameters, so that the scheduling optimization model outputs the distribution quantity and the route of each material, is specifically: According to the production shift, the total working time and the rest time in a day or a shift are determined; According to the total working time and the rest time, the effective time actually available for production is calculated; According to the effective time, the production rate, the preset working parameters, and the preset maintenance frequency parameters, the preset scheduling optimization model is simulated, so that the scheduling optimization model outputs the distribution quantity and the route of each material after simulating the material distribution process under different production conditions; The preset scheduling optimization model is constructed according to production requirement data of different processes in the production line, material characteristic data, and packaging, loading, and unloading of each material, and is specifically: The production requirements of different processes, the material characteristics of different processes, the packaging mode of each material, the loading mode of each material, and the unloading mode of each material are obtained; The production requirements include production capacity, production beat, workstation layout, and staff allocation of different processes; the material characteristics include size, weight, shape, and quantity of each material; the packaging mode includes size, weight limit, and stacking requirement of packaging; the loading mode of each material includes using a forklift, automatically drilling into the bottom of a rack, and unhooking loading; and the unloading mode includes waiting for an employee to unload at a preset workstation control point or a trolley entering a workstation to cooperate with a worker to complete assembly and processing work; According to the production requirements and the material characteristics, an initial scheduling optimization model is constructed; The optimization module is used to adjust the distribution plan of each material according to the distribution quantity and the route of each material. ​ ​ ​ 7. A computer-readable storage medium, characterized in that, The computer readable storage medium comprises a stored computer program, wherein the computer readable storage medium controls a device in which the computer readable storage medium is located to execute the material distribution scheduling optimization method according to any one of claims 1 to 5 when the computer program is running.

8. A terminal device, comprising: The computer readable storage medium comprises a stored computer program, wherein the computer readable storage medium controls a device in which the computer readable storage medium is located to execute the material distribution scheduling optimization method according to any one of claims 1 to 5 when the computer program is running.

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