Scheduling optimization method and device for material distribution, medium and equipment

Abstract

The invention discloses a material distribution scheduling optimization method and device, a medium and equipment. According to the method, the production shift and beat data of each material are acquired, and the preset scheduling optimization model is simulated in combination with the preset working parameters (including the standard processing time of different procedures and the working efficiency of an operator) and the preset overhaul frequency parameters. The model is constructed on the basis of production requirements, material characteristics and material packaging, loading and unloading conditions of different procedures in a production line, and the distribution quantity and route of each material can be output. And the simulation result is used for adjusting the distribution plan of each material so as to optimize the distribution efficiency and respond to the production demand, and ensure the synchronization of the material distribution and the production takt, and the problem that accurate and efficient material scheduling and distribution cannot be performed in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of scheduling optimization of material distribution, and in particular to a scheduling optimization method, device, medium and equipment for material distribution. Background Art

[0002] With the rapid development of automation and intelligence, AGV is widely used in production and manufacturing, especially in material transportation, production and other scenarios. At present, many large manufacturers have chosen to use AGV. AGV is an intelligent mobile robot, mainly used as a means of transportation. It is small and flexible, has a large load capacity, and an adjustable load form. It can be used to transport materials, and can be lifted, lowered, and rotated. It can also be made into various forms and advantages such as traction and unhooking, and it is easy to control.

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

[0004] At present, the material distribution demand of a production line is inconsistent, which is mainly affected by the material characteristics, product characteristics and production line production requirements. Therefore, in terms of material distribution requirements, in order to simplify, the material requirements are generally configured separately according to the different process requirements of different production lines, and then the material configuration routes and carts are planned separately. If there are distribution logistics requirements for multiple processes, there will be multiple production lines configured, which is unbalanced in resource allocation. The most direct point is space allocation. Most of the space in the factory is used for production line layout, and there are very few resources and layout space specially planned for material distribution. Secondly, multiple distribution routes will cause intersections and overlaps between routes, add a lot of avoidance rules, increase the difficulty of distribution, and are not conducive to transportation efficiency. These influences make it impossible for existing technologies to perform accurate and efficient material scheduling and distribution. Summary of the invention

[0005] The present invention provides a scheduling optimization method, device, medium and equipment for material distribution to solve the problem that accurate and efficient material scheduling and distribution cannot be performed in the prior art.

[0006] In a first aspect, the present application provides a scheduling optimization method for material distribution, comprising:

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

[0008] According to the production shift, beat data, preset working parameters and preset maintenance frequency parameters, a 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 based on the production requirement data of different processes in the production line, the material characteristics data, and the packaging, loading and unloading conditions of each material;

[0010] Adjust the distribution plan of each material according to the distribution quantity and route of each material.

[0011] This application obtains the production shift and beat data of each material, and simulates the preset scheduling optimization model in combination with the preset working parameters and maintenance frequency parameters. The model comprehensively 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 quantities and routes. This comprehensive simulation method can ensure that the material distribution plan is synchronized with the actual production needs, reduce waiting and delays in the distribution process, and improve the efficiency of material circulation. Furthermore, 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, this application can achieve more efficient and accurate material distribution, enhance the coordination of the production line, and solve the problem that accurate and efficient material scheduling and distribution cannot be carried out in the prior art.

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

[0013] Obtain the production requirements of different processes in the production line, 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;

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

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

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

[0017] In this preferred embodiment, the present application constructs a preset scheduling optimization model by comprehensively considering the production requirements, material characteristics, and packaging, loading and unloading of materials in different processes in the production line. This method can accurately match the specific needs and material characteristics of each process. The analysis of production requirements ensures that the model can adapt to the production capacity, beat, layout and staffing of different processes, while the consideration of material characteristics ensures that the model can handle the size, weight, shape and quantity of different materials. The detailed analysis of packaging methods, loading methods and unloading methods further optimizes the material handling and storage process. Therefore, the beneficial effect of this comprehensive method is that it can improve the accuracy and efficiency of material distribution, reduce bottlenecks and waste in production, thereby improving overall production efficiency and reducing costs. Through this refined scheduling optimization, the present application enables the production line to better respond to changes, improve the flexibility and adaptability of production, 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 the initial scheduling optimization model, specifically:

[0019] Evaluate the impact of material loading and unloading on efficiency based on the packaging method, including packaging size, weight limit and stacking requirements;

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

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

[0022] This application can evaluate the specific impact of material loading and unloading on efficiency by carefully analyzing the packaging methods of materials, including size, weight restrictions and stacking requirements, thereby identifying possible bottlenecks and optimization points. Further, considering different loading techniques, such as using forklifts, automatically drilling into the bottom of the rack and unhooking loading, this application evaluates the specific impact of these technologies on loading time, which helps to optimize the efficiency of loading operations. Combining these analysis results, as well as the unloading method of materials, this application constructs a preset scheduling optimization model. This model can accurately predict and plan key time nodes and operating steps in the material distribution process, thereby reducing waiting and processing time and improving overall material distribution efficiency. Therefore, the beneficial effect of this method is that it can reduce non-value-added time in production, improve the operating efficiency of the production line, and ultimately achieve cost savings and increased production capacity by accurately controlling and optimizing the loading, transportation and unloading processes of materials.

[0023] As a preferred embodiment of the first aspect, the preset scheduling optimization model is constructed based on the factors affecting the loading and unloading efficiency of the materials, the impact of the various technologies on the loading time and the unloading method, specifically:

[0024] Based on the factors affecting the loading and unloading efficiency of the materials, the impact of the various technologies on the loading time and the unloading methods, a transportation route for planning various materials is constructed;

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

[0026] A preset scheduling optimization model is constructed based on the control point model and the transportation route.

[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 materials, the impact of different loading technologies on loading time, and the specific unloading method. This model can set up control points on the key path of the transportation route according to preset parameters. These control points are used for information feedback and task scheduling of the scheduling system, thereby forming a control point model. Combining 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 every 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 respond to changes in production demand more flexibly, reduce material waiting and handling time, reduce logistics costs, improve the throughput and response speed of the production line, and ultimately achieve a significant increase 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, beat data, preset working parameters and preset maintenance frequency parameters, so that the scheduling optimization model outputs the delivery quantity and route of each material, specifically:

[0029] Determine the total working time and rest time within a day or a shift according to the production shift;

[0030] Based on the total working time and rest time, calculate the effective time actually available for production;

[0031] Calculate the production rate that meets the preset requirements according to the beat data;

[0032] 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 route of each material after simulating the material distribution process under different production conditions;

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

[0034] The preset maintenance frequency parameters include the regular maintenance and repair time of the preset equipment and the preset mobile robot.

[0035] In this preferred implementation, the present application can calculate the effective time that can actually be used for production by determining the total working time and rest time within a day or a shift according to the production shift. Combined with the beat data, that is, the ideal production interval time of each product, the present application can calculate the production rate that meets the preset requirements. 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 a simulation can simulate the material distribution process under different production conditions and output the distribution quantity and route of each material. This simulation method of the present application can ensure that the material distribution plan is synchronized with the actual production demand, reduce waiting and delays in the distribution process, and improve the material circulation 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.

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

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

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

[0039] The preset scheduling optimization model is constructed based on the production requirement data of different processes in the production line, the material characteristics data, and the packaging, loading and unloading conditions of each material;

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

[0041] This device uses three modules to divide the work and coordinate the work to better schedule the distribution of materials. This application obtains the production shift and beat data of each material, and simulates the preset scheduling optimization model in combination with the preset working parameters and maintenance frequency parameters. The model comprehensively 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 quantities and routes. This comprehensive simulation method can ensure that the material distribution plan is synchronized with the actual production needs, reduce waiting and delays in the distribution process, and improve the efficiency of material circulation. Furthermore, 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, this application can achieve more efficient and accurate material distribution, enhance the coordination of the production line, and solve the problem that accurate and efficient material scheduling and distribution cannot be carried out in the prior art.

[0042] In a third aspect, the present application provides a computer-readable storage medium, the computer-readable storage medium including a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute a scheduling optimization method for material distribution as described above. Its beneficial effects are the same as those of the scheduling optimization method for material distribution provided in the first aspect of the present application.

[0043] In a fourth aspect, 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 when the processor executes the computer program, it implements any one of the material distribution scheduling optimization methods described in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 : A flow chart of an embodiment of a scheduling optimization method for material distribution provided in the present application;

[0045] Figure 2 : A structural schematic diagram of an embodiment of each process of the production line provided in this application;

[0046] Figure 3 : A structural diagram of an embodiment of the characteristics and relationships of the processes and materials provided in this application;

[0047] Figure 4 : A structural schematic diagram of an embodiment of a preliminary loading and unloading model provided in this application;

[0048] Figure 5 : A structural diagram of an embodiment of a scheduling optimization device for material distribution provided in this application. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] Embodiment 1

[0051] Please refer to Figure 1 , which is a scheduling optimization method for material distribution provided by an embodiment of the present invention.

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

[0053] S01: Get the production shift and cycle data of each material.

[0054] S02: According to the production shift, beat 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;

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

[0056] As a preferred embodiment of the first embodiment, the preset scheduling optimization model is constructed based on 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 production requirements for 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 a straight line, and the production line is produced in an assembly line manner;

[0059] (2) The current one-line processing production line has a total of 6 processes, each process corresponds to a type of material (the weight, size and quantity of each type of material are consistent), the number of workstations in different processes is inconsistent, and the production staff configured are also different, such as Figure 2 As shown;

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

[0061] (1) The materials in different processes have different characteristics, mainly classified by shape, weight and size. According to the characteristics of the six processes, the characteristics and relationships between the processes and materials are sorted out, such as 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 nuts and screws, wire harnesses in strips, and large assembly parts. Among them, the last process 6 is quality inspection, which is mainly inspected by operators using quality inspection tools. Process 6 (station 11) does not require the delivery of parts;

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

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

[0065] ② There 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 unhooking loading, the trolley is aligned with the unhooking, and pulls the rack forward;

[0066] ③ There are two ways for the trolley to unload materials to the workstation. One is to go to the workstation control point, wait for the employee to unload the materials, and then the trolley returns with the material rack. The other is for the trolley to enter the workstation, cooperate with the worker to complete the assembly and processing work at the workstation, and then return with the material rack.

[0067] Furthermore, simulation is performed based on the collected relevant materials, and the simulation process is as follows:

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

[0069] ① Establish a workstation model: Establish a simulated three-dimensional solid model and a processor model to represent each workstation. The average processing time of each workstation is adjusted to represent the production time of the workstation.

[0070] ② Establish a workstation operator model: Establish a simulated three-dimensional solid model and a human body model. The job of each employee is to assist the processor in completing the processing task, and establish a matching model between employees and workstations;

[0071] ③ Establish a path model: Establish a path model. The path guides the transportation route of the vehicle. There are one-way and two-way routes. 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, to avoid frequent avoidance problems on the opposite route, the entire route is designed as a large ring route. On the other hand, multiple branches are set on the unavoidable opposite road, and the vehicle can choose to wait on the branch path;

[0072] ④ Establish a control point model: add control points, build them on the path, indicate the current point position, set up control points on the key path, and then write parameters on the control points to realize information feedback between AGV and the scheduling system;

[0073] (2) Simulate materials and racks:

[0074] ① Simulate material generation: By establishing a material generator, set the size and quantity of the material according to the material arrival schedule. The material generator will generate different materials according to the set parameters. In order to facilitate distinction, different color parameters can be set for different materials. At the same time, each material is given a model to represent the material type;

[0075] ②Simulation of rack generation: By establishing a rack generator, different rack appearance parameters are set for differentiation. At the same time, in order to match the material, the color and model of the rack are set to be consistent with the material.

[0076] ③ Combination: By establishing a processing processor, when each material reaches a certain quantity and matches a rack, the material and the rack are combined;

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

[0078] ① Establish an AGV simulation model: The simulation system has a pre-set AGV model, which can adjust the speed, acceleration, size, power consumption and other states. The number of cars is initialized to the maximum upper limit that the layout can accommodate, and each car is numbered. The car can stop at the control point of the path, and the scheduling system can obtain the car number corresponding to the control point;

[0079] ② Scheduling system model: Establish a three-dimensional entity simulation model and establish a computer / host computer scheduling system;

[0080] ③ Material ordering process model: Establish a material ordering model. This process is mainly a way of information transmission. There is no three-dimensional entity model. Establish a custom logic tool in the simulation model tool interface, initialize the settings, and establish an information transmission parameter for each workstation to interact with the scheduling system. When the material of the current workstation can maintain the production line for less than 30 minutes, start sending material ordering tasks to the scheduling system. The priority of normal task arrangement is based on the order of precedence. If materials are ordered at the same time, the scheduling 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 tasks of three processes at one time. According to the material calling task arrangement, three vehicles are dispatched to the loading points of three processes at one time to perform the loading tasks. When the vehicle arrives at the loading control point, in order to facilitate distinction, the animations of using a forklift, automatically identifying unhooking, and automatically drilling to the bottom of the rack are simplified. The difference in loading methods lies in the inconsistency of loading time. Therefore, in this case, the loading methods are uniformly distinguished by loading time.

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

[0083] Establish a preliminary loading and unloading model such as Figure 4 shown.

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

[0085] The process flow of the simulation model is established to connect the simulation path, three-dimensional solid model, scheduling system and related parameters in series according to the entire production process to establish a logical system that conforms to a complete production process.

[0086] In this preferred embodiment, the present application constructs a preset scheduling optimization model by comprehensively considering the production requirements, material characteristics, and packaging, loading and unloading of materials in different processes in the production line. This method can accurately match the specific needs and material characteristics of each process. The analysis of production requirements ensures that the model can adapt to the production capacity, beat, layout and staffing of different processes, while the consideration of material characteristics ensures that the model can handle the size, weight, shape and quantity of different materials. The detailed analysis of packaging methods, loading methods and unloading methods further optimizes the material handling and storage process. Therefore, the beneficial effect of this comprehensive method is that it can improve the accuracy and efficiency of material distribution, reduce bottlenecks and waste in production, thereby improving overall production efficiency and reducing costs. Through this refined scheduling optimization, the present application enables the production line to better respond to changes, improve the flexibility and adaptability of production, and ultimately achieve more efficient production operations.

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

[0088] Import the EXCEL shifts and beats in the timetable of the simulation model interface to obtain the average production line efficiency under a single shift and the production efficiency of each process and workstation;

[0089] For all workstation processors, set the working and maintenance frequency, maintenance time and other related parameters in the property interface;

[0090] Balance the number of control points in the model. The control point is the exploration point for the car to move forward to perform tasks, and it is also the carrier of signal interaction between the car and the scheduling system. According to the size and spatial layout of the car, combined with the actual navigation method of the car, the number of control points in the model should be reasonably set.

[0091] After the simulation is completed, the production line efficiency, the production efficiency of each workstation, the average loading time of the trolley, etc. are derived; compared with the historical production efficiency of the production line, whether it meets the normal production line requirements.

[0092] In this preferred implementation, the present application can calculate the effective time that can actually be used for production by determining the total working time and rest time within a day or a shift according to the production shift. Combined with the beat data, that is, the ideal production interval time of each product, the present application can calculate the production rate that meets the preset requirements. 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 a simulation can simulate the material distribution process under different production conditions and output the distribution quantity and route of each material. This simulation method of the present application can ensure that the material distribution plan is synchronized with the actual production demand, reduce waiting and delays in the distribution process, and improve the material circulation 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 the first embodiment, the distribution plan of each material is adjusted according to the distribution quantity and route of each material, specifically:

[0095] According to the simulation results, the lower limit of the number of delivery carts is required to meet the material demand under different beats to meet the production efficiency requirements of the production line;

[0096] If the beat is constant and the production line efficiency is met, the lower limit of the material call at different workstations will change, and the lower limit of the number of delivery carts will be required;

[0097] If the production line efficiency is to be met, the lower limit of material calls at different workstations remains unchanged, and the production rhythm is to be increased, a lower limit on the number of delivery carts is required.

[0098] This application obtains the production shift and beat data of each material, and simulates the preset scheduling optimization model in combination with the preset working parameters and maintenance frequency parameters. The model comprehensively 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 quantities and routes. This comprehensive simulation method can ensure that the material distribution plan is synchronized with the actual production needs, reduce waiting and delays in the distribution process, and improve the efficiency of material circulation. Furthermore, 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, this application can achieve more efficient and accurate material distribution, enhance the coordination of the production line, and solve the problem that accurate and efficient material scheduling and distribution cannot be carried out in the prior art.

[0099] Embodiment 2

[0100] Please refer to Figure 5 , which is a material distribution scheduling optimization device provided in an embodiment of the present application.

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

[0102] The acquisition module 10 is used to acquire the production shift and beat data of each material.

[0103] The simulation module 20 is used to simulate the preset scheduling optimization model according to the production shift, beat data, preset working parameters and preset maintenance frequency parameters, so that the scheduling optimization model outputs the delivery quantity and route of each material;

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

[0105] As a preferred embodiment of the second embodiment, the preset scheduling optimization model is constructed based on 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:

[0106] 1. Obtain production requirements for 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 a straight line, and the production line is produced in an assembly line manner;

[0108] (2) The current one-line processing production line has a total of 6 processes, each process corresponds to a type of material (the weight, size and quantity of each type of material are consistent), the number of workstations in different processes is inconsistent, and the production staff configured are also different, such as Figure 2 As shown;

[0109] 2. Obtain material characteristics of different processes:

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

[0111] The material types of this production line are roughly divided into four types, all of which are parts packed in boxes, including nuts and screws, wire harnesses in strips, and large assembly parts. Among them, the last process 6 is quality inspection, which is mainly inspected by operators using quality inspection tools. Process 6 (station 11) does not require the delivery of parts;

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

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

[0114] ② There 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 unhooking loading, the trolley is aligned with the unhooking, and pulls the rack forward;

[0115] ③ There are two ways for the trolley to unload materials to the workstation. One is to go to the workstation control point, wait for the employee to unload the materials, and then the trolley returns with the material rack. The other is for the trolley to enter the workstation, cooperate with the worker to complete the assembly and processing work at the workstation, and then return with the material rack.

[0116] Furthermore, simulation is performed based on the collected relevant materials, and the simulation process is as follows:

[0117] (1) Establish a production line model:

[0118] ① Establish a workstation model: Establish a simulated three-dimensional solid model and a processor model to represent each workstation. The average processing time of each workstation is adjusted to represent the production time of the workstation.

[0119] ② Establish a workstation operator model: Establish a simulated three-dimensional solid model and a human body model. The job of each employee is to assist the processor in completing the processing task, and establish a matching model between employees and workstations;

[0120] ③ Establish a path model: Establish a path model. The path guides the transportation route of the vehicle. There are one-way and two-way routes. 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, to avoid frequent avoidance problems on the opposite route, the entire route is designed as a large ring route. On the other hand, multiple branches are set on the unavoidable opposite road, and the vehicle can choose to wait on the branch path;

[0121] ④ Establish a control point model: add control points, build them on the path, indicate the current point position, set up control points on the key path, and then write parameters on the control points to realize information feedback between AGV and the scheduling system;

[0122] (2) Simulate materials and racks:

[0123] ① Simulate material generation: By establishing a material generator, set the size and quantity of the material according to the material arrival schedule. The material generator will generate different materials according to the set parameters. In order to facilitate distinction, different color parameters can be set for different materials. At the same time, each material is given a model to represent the material type;

[0124] ②Simulation of rack generation: By establishing a rack generator, different rack appearance parameters are set for differentiation. At the same time, in order to match the material, the color and model of the rack are set to be consistent with the material.

[0125] ③ Combination: By establishing a processing processor, when each material reaches a certain quantity and matches a rack, the material and the rack are combined;

[0126] (3) Simulate the model of loading and unloading materials:

[0127] ① Establish an AGV simulation model: The simulation system has a pre-set AGV model, which can adjust the speed, acceleration, size, power consumption and other states. The number of cars is initialized to the maximum upper limit that the layout can accommodate, and each car is numbered. The car can stop at the control point of the path, and the scheduling system can obtain the car number corresponding to the control point;

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

[0129] ③ Material ordering process model: Establish a material ordering model. This process is mainly a way of information transmission. There is no three-dimensional entity model. Establish a custom logic tool in the simulation model tool interface, initialize the settings, and establish an information transmission parameter for each workstation to interact with the scheduling system. When the material of the current workstation can maintain the production line for less than 30 minutes, start sending material ordering tasks to the scheduling system. The priority of normal task arrangement is based on the order of precedence. If materials are ordered at the same time, the scheduling 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;

[0130] ④ Execute the loading process: This model can execute the material tasks of three processes at one time. According to the material calling task arrangement, three vehicles are dispatched to the loading points of three processes at one time to perform the loading tasks. When the vehicle arrives at the loading control point, in order to facilitate distinction, the animations of using a forklift, automatically identifying unhooking, and automatically drilling to the bottom of the rack are simplified. The difference in loading methods lies in the inconsistency of loading time. Therefore, in this case, the loading methods are uniformly distinguished by loading time.

[0131] ⑤Execute unloading simulation: the trolley goes to the unloading station and executes unloading requirements according to the requirements of different stations;

[0132] Establish a preliminary loading and unloading model such as Figure 4 shown.

[0133] (4) Process flow of model building:

[0134] The process flow of the simulation model is established to connect the simulation path, three-dimensional solid model, scheduling system and related parameters in series according to the entire production process to establish a logical system that conforms to a complete production process.

[0135] In this preferred embodiment, the present application constructs a preset scheduling optimization model by comprehensively considering the production requirements, material characteristics, and packaging, loading and unloading of materials in different processes in the production line. This method can accurately match the specific needs and material characteristics of each process. The analysis of production requirements ensures that the model can adapt to the production capacity, beat, layout and staffing of different processes, while the consideration of material characteristics ensures that the model can handle the size, weight, shape and quantity of different materials. The detailed analysis of packaging methods, loading methods and unloading methods further optimizes the material handling and storage process. Therefore, the beneficial effect of this comprehensive method is that it can improve the accuracy and efficiency of material distribution, reduce bottlenecks and waste in production, thereby improving overall production efficiency and reducing costs. Through this refined scheduling optimization, the present application enables the production line to better respond to changes, improve the flexibility and adaptability of production, and ultimately achieve more efficient production operations.

[0136] As a preferred embodiment of the second embodiment, the preset scheduling optimization model is simulated according to the production shift, beat data, preset working parameters and preset maintenance frequency parameters, so that the scheduling optimization model outputs the delivery quantity and route of each material, specifically:

[0137] Import the EXCEL shifts and beats in the timetable of the simulation model interface to obtain the average production line efficiency under a single shift and the production efficiency of each process and workstation;

[0138] For all workstation processors, set the working and maintenance frequency, maintenance time and other related parameters in the property interface;

[0139] Balance the number of control points in the model. The control point is the exploration point for the car to move forward to perform tasks, and it is also the carrier of signal interaction between the car and the scheduling system. According to the size and spatial layout of the car, combined with the actual navigation method of the car, the number of control points in the model should be reasonably set.

[0140] After the simulation is completed, the production line efficiency, the production efficiency of each workstation, the average loading time of the trolley, etc. are derived; compared with the historical production efficiency of the production line, whether it meets the normal production line requirements.

[0141] In this preferred implementation, the present application can calculate the effective time that can actually be used for production by determining the total working time and rest time within a day or a shift according to the production shift. Combined with the beat data, that is, the ideal production interval time of each product, the present application can calculate the production rate that meets the preset requirements. 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 a simulation can simulate the material distribution process under different production conditions and output the distribution quantity and route of each material. This simulation method of the present application can ensure that the material distribution plan is synchronized with the actual production demand, reduce waiting and delays in the distribution process, and improve the material circulation 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.

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

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

[0144] According to the simulation results, the lower limit of the number of delivery carts is required to meet the material demand under different beats to meet the production efficiency requirements of the production line;

[0145] If the beat is constant and the production line efficiency is met, the lower limit of the material call at different workstations will change, and the lower limit of the number of delivery carts will be required;

[0146] If the production line efficiency is to be met, the lower limit of material calls at different workstations remains unchanged, and the production rhythm is to be increased, a lower limit on the number of delivery carts is required.

[0147] This device uses three modules to divide the work and coordinate the work to better schedule the distribution of materials. This application obtains the production shift and beat data of each material, and simulates the preset scheduling optimization model in combination with the preset working parameters and maintenance frequency parameters. The model comprehensively 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 quantities and routes. This comprehensive simulation method can ensure that the material distribution plan is synchronized with the actual production needs, reduce waiting and delays in the distribution process, and improve the efficiency of material circulation. Furthermore, 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, this application can achieve more efficient and accurate material distribution, enhance the coordination of the production line, and solve the problem that accurate and efficient material scheduling and distribution cannot be carried out in the prior art.

[0148] Embodiment three:

[0149] The embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the scheduling optimization method for material distribution;

[0150] Wherein, the scheduling optimization method for material distribution, if implemented in the form of a software functional unit and used as an independent product, can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0151] Embodiment 4

[0152] The present application provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements any one of the scheduling optimization methods for material distribution as described in Example 1.

[0153] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A scheduling optimization method for material distribution, characterized in that: include: Obtain production shift and beat data for each material; According to the production shift, beat data, preset working parameters and preset maintenance frequency parameters, a preset scheduling optimization model is simulated so that the scheduling optimization model outputs the delivery quantity and route of each material; The preset scheduling optimization model is constructed based on the production requirement data of different processes in the production line, the material characteristics data, and the packaging, loading and unloading conditions of each material; Adjust the distribution plan of each material according to the distribution quantity and route of each material.

2. The scheduling optimization method for material distribution according to claim 1 is characterized in that: The preset scheduling optimization model is constructed based on the production requirement data of different processes in the production line, material characteristic data, and the packaging, loading and unloading conditions of each material, specifically: Obtain the production requirements of different processes in the production line, 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; Among them, the production requirements include the production capacity, production rhythm, workstation layout and staff allocation of different processes; the material characteristics include the size, weight, shape and quantity of each material; the packaging method includes the size, weight limit and stacking requirements of the packaging; the loading method of each material includes using a forklift, automatically drilling into the bottom of the rack and unhooking loading; the unloading method includes waiting for employees to unload at a preset workstation control point or a trolley entering the workstation to cooperate with workers to complete assembly and processing work; According to the production requirements and material characteristics, an initial scheduling optimization model is constructed; According to the packaging method, loading method, unloading method and the initial scheduling optimization model, a preset scheduling optimization model is constructed.

3. The scheduling optimization method for material distribution according to claim 2 is characterized in that: The preset scheduling optimization model is constructed according to the packaging method, loading method, unloading method and the initial scheduling optimization model, specifically: Evaluate the impact of material loading and unloading on efficiency based on the packaging method, including packaging size, weight limit and stacking requirements; According to the loading methods of each material, including forklift, automatic drilling into the bottom of the rack and unhooking loading, the impact of each technology on loading time is evaluated; According to the impact of the loading and unloading of the materials on the efficiency, the impact of the various technologies on the loading time and the unloading method, a preset scheduling optimization model is constructed.

4. The scheduling optimization method for material distribution according to claim 3 is characterized in that: The preset scheduling optimization model is constructed based on the factors affecting the loading and unloading efficiency of the materials, the impact of each technology on the loading time and the unloading method, specifically: Based on the factors affecting the loading and unloading efficiency of the materials, the impact of the various technologies on the loading time and the unloading methods, a transportation route for planning various materials is constructed; According to preset parameters, various control points for information feedback and task scheduling of the scheduling system are established on the preset critical path of the transportation route to obtain a control point model; A preset scheduling optimization model is constructed based on the control point model and the transportation route.

5. The scheduling optimization method for material distribution according to claim 1 is characterized in that: According to the production shift, beat 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, specifically: Determine the total working time and rest time within a day or a shift according to the production shift; Based on the total working time and rest time, calculate the effective time actually available for production; According to the beat data, a production rate that meets preset requirements 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 simulates the material distribution process under different production conditions and then outputs the distribution quantity and route of each material.

6. The scheduling optimization method for material distribution according to claim 5 is characterized in that: The preset working parameters include standard processing time for different working procedures and preset working efficiency of operators.

7. The scheduling optimization method for material distribution according to claim 5 is characterized in that: The preset maintenance frequency parameters include the regular maintenance and repair time of the preset equipment and the preset mobile robot.

8. A scheduling optimization device for material distribution, characterized in that: It includes acquisition module, simulation module and optimization module; The acquisition module is used to obtain the production shift and beat data of each material; The simulation module is used to simulate the preset scheduling optimization model according to the production shift, beat data, preset working parameters and preset maintenance frequency parameters, so that the scheduling optimization model outputs the delivery quantity and route of each material; The preset scheduling optimization model is constructed based on the production requirement data of different processes in the production line, the material characteristics data, and the packaging, loading and unloading conditions of each material; The optimization module is used to adjust the distribution plan of each material according to the distribution quantity and route of each material.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the scheduling optimization method for material distribution according to any one of claims 1 to 7.

10. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the scheduling optimization method for material distribution as described in any one of claims 1 to 7 is implemented.

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