Intelligent material transportation control system of smart factory

Abstract

The invention provides an intelligent material transportation control system of a smart factory, and relates to the technical field of transportation path planning, material transportation demand information in the smart factory is acquired, and all material demand points corresponding to a target material transportation vehicle are extracted from the material transportation demand information; obtaining transportation parameters of the target material transport vehicle, determining material distribution costs between the target material transport vehicle and each material demand point according to the transportation parameters, and constructing a transportation planning path according to all the material distribution costs; constructing a distribution penalty window, and determining a distribution penalty coefficient corresponding to each material demand point based on the distribution penalty window; and determining the path priority of each material demand point according to the corresponding material delivery cost and the corresponding delivery penalty coefficient, and updating the transportation planning path according to the path priority of each material demand point to obtain a material transportation path. And the distribution path of the material transport vehicle is efficiently planned.

Description

Technical Field

[0001] The present application relates to the technical field of transportation route planning, and more specifically, to an intelligent material transportation control system for a smart factory. Background Art

[0002] The intelligent material transportation control system of the smart factory is an efficient logistics management system that integrates the Internet of Things, big data analysis, artificial intelligence and automation technology, aiming to improve the accuracy and efficiency of material distribution on the production line. The system uses a variety of advanced technologies to achieve intelligent control of the entire process, including real-time acquisition and analysis of material demand information, dynamic path planning and task scheduling, coordinated control of automated transportation equipment, and dynamic response capabilities in a variety of complex scenarios.

[0003] Although intelligent material transportation control systems have significant efficiency advantages, the transportation network of a smart factory is usually a dynamic, multi-constrained complex system that includes not only the distribution of material demand points, but also multiple variables such as the performance of transportation equipment, path congestion, and energy consumption constraints. These factors interact with each other, making it difficult for traditional path optimization algorithms to meet actual needs. Therefore, how to efficiently plan the distribution path of material transport vehicles when distributing materials in smart factories is a difficult problem faced by the industry. Summary of the invention

[0004] The present application provides an intelligent material transportation control system for a smart factory, which can efficiently plan the distribution routes of material transport vehicles when distributing materials in the smart factory.

[0005] The present application provides an intelligent material transportation control system for a smart factory, the control system comprising:

[0006] A demand acquisition module is used to obtain material transportation demand information in the smart factory, and extract all material demand points corresponding to the target material transport vehicle from the material transportation demand information;

[0007] A path planning module is used to obtain the transportation parameters of the target material transport vehicle, determine the material distribution cost between the target material transport vehicle and each material demand point according to the transportation parameters, and construct the transportation planning path of the target material transport vehicle according to all the material distribution costs;

[0008] A distribution penalty module is used to construct a distribution penalty window for a target material transport vehicle when transporting materials, and determine a distribution penalty coefficient corresponding to each material demand point in the transportation planning path based on the distribution penalty window;

[0009] The operation path determination module is used to determine the path priority of each material demand point according to the corresponding material distribution cost and the corresponding distribution penalty coefficient, and update the transportation planning path according to the path priority of each material demand point to obtain the material transportation path of the target material transport vehicle.

[0010] In this embodiment, the material transportation demand information in the smart factory is obtained from the production planning system of the smart factory.

[0011] In this embodiment, extracting all material demand points corresponding to the target material transport vehicle from the material transport demand information specifically includes:

[0012] Get the unique ID of the target material transport vehicle;

[0013] Determine the transport responsible block of the target material transport vehicle in the smart factory according to the unique identifier;

[0014] Extracting all material demand points within the transport responsible area from the material transport demand information;

[0015] All material demand points within the transport responsible area are taken as all material demand points corresponding to the target material transport vehicle.

[0016] In this embodiment, the transport parameters of the target material transport vehicle are acquired through an intelligent sensor network.

[0017] In this embodiment, determining the material distribution cost between the target material transport vehicle and each material demand point according to the transportation parameters specifically includes:

[0018] Extracting the transport speed, transport starting point and transport load of the target material transport vehicle from the transport parameters;

[0019] For each material demand point, obtain the location information of the material demand point;

[0020] Determine the transportation distance cost between the target material transport vehicle and the material demand point according to the transportation starting point and the location information;

[0021] Determine the transportation time cost between the target material transport vehicle and the material demand point by using the transportation speed and the transportation distance cost;

[0022] The transportation energy consumption cost between the target material transport vehicle and the material demand point is determined based on the transportation load and the transportation distance cost:

[0023] The material distribution cost between the target material transport vehicle and the material demand point is determined according to the transport distance cost, the transport time cost and the transport energy consumption cost, and then the material distribution cost between the target material transport vehicle and each material demand point is obtained.

[0024] In this embodiment, constructing the transportation planning path of the target material transport vehicle according to all material distribution costs is to connect all material demand points in ascending order according to the material distribution costs, and then obtain the transportation planning path of the target material transport vehicle.

[0025] In this embodiment, constructing a delivery penalty window for a target material transport vehicle when transporting materials specifically includes:

[0026] Construct a distribution penalty function for the target material transport vehicle when transporting materials;

[0027] A delivery penalty window is constructed for the target material transport vehicle when transporting materials according to the delivery penalty function.

[0028] In this embodiment, determining the distribution penalty coefficient corresponding to each material demand point in the transportation planning path based on the distribution penalty window specifically includes:

[0029] For each material demand point in the transportation planning path, extract the material demand time period of the material demand point from the material transportation demand information;

[0030] Determine the delivery time point when the target transport vehicle arrives at the material demand point;

[0031] The distribution penalty coefficient corresponding to the material demand point is determined according to the material demand time period, the distribution time point and the distribution penalty window, and then the distribution penalty coefficient corresponding to each material demand point in the transportation planning path is obtained.

[0032] In this embodiment, determining the path priority of each material demand point according to the corresponding material distribution cost and the corresponding distribution penalty coefficient specifically includes:

[0033] Determine the cost weight based on all material delivery costs;

[0034] Determine the penalty weight based on all delivery penalty coefficients;

[0035] For each material demand point in the transportation planning path, the path priority of the material demand point is determined by the cost weight, the penalty weight, the material distribution cost corresponding to the material demand point and the distribution penalty coefficient, thereby obtaining the path priority of each material demand point.

[0036] In this embodiment, updating the transportation planning path according to the path priority of each material demand point is to connect each material demand point in the transportation planning path in descending order according to the path priority, thereby obtaining the material transportation path of the target material transport vehicle.

[0037] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0038] The material transportation demand information in the smart factory is obtained through the demand acquisition module, and all material demand points corresponding to the target material transport vehicle are extracted from the material transportation demand information; the transportation parameters of the target material transport vehicle are obtained through the path planning module, and the material distribution cost between the target material transport vehicle and each material demand point is determined based on the transportation parameters, and the transportation planning path of the target material transport vehicle is constructed based on all the material distribution costs; the distribution penalty window of the target material transport vehicle when transporting materials is constructed through the distribution penalty module, and the distribution penalty coefficient corresponding to each material demand point in the transportation planning path is determined based on the distribution penalty window; the operation path determination module determines the path priority of each material demand point based on the corresponding material distribution cost and the corresponding distribution penalty coefficient, and updates the transportation planning path according to the path priority of each material demand point to obtain the material transportation path of the target material transport vehicle.

[0039] It can be seen that in this application, firstly, by accurately calculating and optimizing the material distribution cost, it can ensure that the material transport vehicle completes the task in the shortest and most energy-efficient way, thereby reducing the overall transportation time; then, by constructing a distribution penalty window and calculating the distribution penalty coefficient based on the distribution penalty window, the smart factory can achieve accurate scheduling and path optimization in the material transportation process. The distribution penalty window can help the system accurately set the arrival time range and penalty degree of each material demand point, ensure that the material transport vehicle arrives at the target location within the appropriate time period, and the calculation of the distribution penalty coefficient further helps to optimize the path planning; finally, in the smart factory, by determining the path priority and updating the transportation planning path according to the material distribution cost and the distribution penalty coefficient, not only can the distribution path of the material transport vehicle be efficiently planned, but also the material transportation efficiency can be improved and the cost can be reduced.

[0040] In summary, the technical solution adopted in this application can efficiently plan the distribution routes of material transport vehicles when distributing materials in smart factories. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0042] Figure 1 It is a module structure diagram of the intelligent material transportation control system of the smart factory provided by this application;

[0043] Figure 2 is an exemplary flow chart for determining the material distribution cost between a target material transport vehicle and each material demand point according to the present application;

[0044] Figure 3 It is an exemplary flow chart for constructing a delivery penalty window for a target material transport vehicle when transporting materials according to the present application. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0046] The embodiment of the present application provides an intelligent material transportation control system for a smart factory, the core of which is to obtain the material transportation demand information in the smart factory through a demand acquisition module, extract all material demand points corresponding to the target material transport vehicle from the material transportation demand information; obtain the transportation parameters of the target material transport vehicle through a path planning module, determine the material distribution cost between the target material transport vehicle and each material demand point based on the transportation parameters, and construct the transportation planning path of the target material transport vehicle based on all the material distribution costs; construct the distribution penalty window of the target material transport vehicle when transporting materials through a distribution penalty module, and determine the distribution penalty coefficient corresponding to each material demand point in the transportation planning path based on the distribution penalty window; the operation path determination module determines the path priority of each material demand point based on the corresponding material distribution cost and the corresponding distribution penalty coefficient, and updates the transportation planning path according to the path priority of each material demand point to obtain the material transportation path of the target material transport vehicle. The above scheme can be used to efficiently plan the distribution path of the material transport vehicle when the smart factory distributes materials.

[0047] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 As shown, this figure is a module structure diagram of an intelligent material transportation control system of a smart factory according to this embodiment of the present application. The response system includes: a demand acquisition module 100, a path planning module 200, a distribution penalty module 300 and an operation path determination module 400, which are respectively described as follows:

[0048] The demand acquisition module 100 is used to acquire material transportation demand information in the smart factory, and extract all material demand points corresponding to the target material transport vehicle from the material transportation demand information.

[0049] In specific implementation, the material transportation demand information in the smart factory can be obtained from the production planning system of the smart factory; it should be noted that in this application, the material transportation demand information includes detailed information on multiple transportation blocks in the smart factory and material demand points in each block, and the detailed information includes the location information of the material demand point, production progress, material demand time period and required materials, etc., among which the material demand point refers to the production line in the smart factory; the production planning system (MES, Manufacturing Execution System) is the core system in the smart factory for managing and scheduling production activities.

[0050] In this embodiment, all material demand points corresponding to the target material transport vehicle may be extracted from the material transport demand information in the following manner, namely:

[0051] Get the unique ID of the target material transport vehicle;

[0052] Determine the transport responsible block of the target material transport vehicle in the smart factory according to the unique identifier;

[0053] Extracting all material demand points within the transport responsible area from the material transport demand information;

[0054] All material demand points within the transport responsible area are taken as all material demand points corresponding to the target material transport vehicle.

[0055] In the specific implementation, first, the unique identification of the target material transport vehicle can be obtained in the vehicle management system through the query interface, wherein the unique identification (such as vehicle ID) is the core information for distinguishing the material transport vehicle; then, the transport responsible block of the target material transport vehicle in the smart factory can be determined according to the unique identification, that is, the transport block that the target material transport vehicle is responsible for can be queried in the production planning system based on the unique identification of the target material transport vehicle, that is, the transport responsible block of the target material transport vehicle in the smart factory; then, all material demand points within the transport responsible block can be extracted from the material transportation demand information by traversal; finally, all material demand points within the transport responsible block can be used as all material demand points corresponding to the target material transport vehicle.

[0056] The path planning module 200 is used to obtain the transportation parameters of the target material transport vehicle, determine the material distribution cost between the target material transport vehicle and each material demand point based on the transportation parameters, and construct the transportation planning path of the target material transport vehicle based on all the material distribution costs.

[0057] In a specific implementation, the transportation parameters of the target material transport vehicle may be acquired through an intelligent sensor network, wherein the transportation parameters include the transportation speed, transportation starting point and transportation load of the target material transport vehicle.

[0058] Preferably, in this embodiment, reference Figure 2 As shown, this figure is an exemplary flow chart of determining the material distribution cost between the target material transport vehicle and each material demand point in an embodiment of the present application. In this embodiment, the material distribution cost between the target material transport vehicle and each material demand point is determined based on the transportation parameters, which can be implemented by the following steps:

[0059] In step S21, the transport speed, transport starting point and transport load of the target material transport vehicle are extracted from the transport parameters;

[0060] In step S22, for each material demand point, the location information of the material demand point is obtained;

[0061] In step S23, the transportation distance cost between the target material transport vehicle and the material demand point is determined according to the transportation starting point and the location information;

[0062] In step S24, the transportation time cost between the target material transport vehicle and the material demand point is determined by the transportation speed and the transportation distance cost;

[0063] In step S25, the transportation energy consumption cost between the target material transport vehicle and the material demand point is determined based on the transportation load and the transportation distance cost:

[0064] In step S26, the material distribution cost between the target material transport vehicle and the material demand point is determined based on the transportation distance cost, the transportation time cost and the transportation energy consumption cost, and then the material distribution cost between the target material transport vehicle and each material demand point is obtained.

[0065] In specific implementation, first, the transportation speed, transportation starting point and transportation load of the target material transport vehicle can be extracted from the transportation parameters; then, for each material demand point, the location information of the material demand point can be obtained in the material transportation demand information, and the location information includes the coordinates of the material demand point in the smart factory; then, the transportation distance cost between the target material transport vehicle and the material demand point can be determined according to the transportation starting point and location information, wherein the transportation distance cost represents the distance cost incurred by the target material transport vehicle to reach the material demand point, and the Euclidean distance between the target material transport vehicle and the material demand point can be calculated based on the transportation starting point and location information, and the result can be used as the transportation distance cost between the target material transport vehicle and the material demand point.

[0066] In addition, in specific implementation, the transportation time cost between the target material transport vehicle and the material demand point can be determined by the transportation speed and transportation distance cost, wherein the transportation time cost represents the time cost generated by the target material transport vehicle reaching the material demand point, and the ratio of the transportation distance cost to the transportation speed can be used as the transportation time cost between the target material transport vehicle and the material demand point; then, the transportation energy consumption cost between the target material transport vehicle and the material demand point can be determined based on the transportation load and transportation distance cost, wherein the transportation energy consumption cost represents the energy consumption cost generated by the target material transport vehicle reaching the material demand point. In actual implementation, the transportation energy consumption cost can be determined by the following formula:

[0067] λ i =d i (W*C+B)

[0068] Among them, λ i represents the transportation energy cost between the target material transport vehicle and the i-th material demand point, d i represents the transportation distance cost between the target material transport vehicle and the i-th material demand point, W represents the transportation load of the target material transport vehicle, C represents the unit load energy consumption coefficient, B represents the empty basic energy consumption coefficient, and the unit load energy consumption coefficient C and the empty basic energy consumption coefficient B can be obtained from the user manual of the target material transport vehicle; finally, the material distribution cost between the target material transport vehicle and the material demand point can be determined based on the transportation distance cost, transportation time cost and transportation energy consumption cost, among which the material distribution cost represents the comprehensive cost generated by the target material transport vehicle distributing materials to the material demand point, and the transportation distance cost, transportation time cost and transportation energy consumption cost can be weighted and summed, and the result can be used as the material distribution cost between the target material transport vehicle and the material demand point, among which the weights corresponding to the transportation distance cost, transportation time cost and transportation energy consumption cost can be set through historical experience and data analysis. The material distribution cost between the target material transport vehicle and each material demand point can be obtained in the above way.

[0069] In this embodiment, constructing the transportation planning path of the target material transport vehicle based on all material distribution costs is to connect all material demand points in ascending order according to the material distribution costs, and then obtain the transportation planning path of the target material transport vehicle; it should be noted that the material demand points can be sorted according to the material distribution cost, and the goal is to sort the material demand points according to the material distribution cost from small to large, to ensure that the path planning starts from the most convenient distribution, so that the target material transport vehicle will travel on the path with the lowest material distribution cost, that is, on the transportation planning path.

[0070] It should be noted that by accurately calculating and optimizing the material distribution cost, it can ensure that the material transport vehicle completes the task in the shortest and most energy-efficient way, thereby reducing the overall transportation time and improving the overall efficiency. Based on reasonable path planning, it can achieve efficient scheduling of the target material transport vehicle, thereby efficiently managing and scheduling hundreds of transportation tasks, ensuring that each transport vehicle can work efficiently according to the predetermined route.

[0071] The distribution penalty module 300 is used to construct a distribution penalty window for the target material transport vehicle when transporting materials, and determine the distribution penalty coefficient corresponding to each material demand point in the transportation planning path based on the distribution penalty window.

[0072] Preferably, in this embodiment, reference Figure 2 As shown, this figure is an exemplary flow chart of constructing a delivery penalty window for a target material transport vehicle when transporting materials in an embodiment of the present application. In this embodiment, constructing a delivery penalty window for a target material transport vehicle when transporting materials can be implemented by the following steps:

[0073] First, in step S31, a distribution penalty function of the target material transport vehicle when transporting materials is constructed;

[0074] Then, in step S32, a delivery penalty window of the target material transport vehicle when transporting materials is constructed according to the delivery penalty function.

[0075] In the specific implementation, first, a distribution penalty function of the target material transport vehicle when transporting materials can be constructed. In the actual implementation, the distribution penalty function can be determined by the following formula:

[0076]

[0077] Among them, F(t) represents the distribution penalty function, Max represents the maximum value of the distribution penalty function, the maximum value of the distribution penalty function in this application is 1, t represents the distribution time point when the target transport vehicle arrives at the material demand point, a and b represent the lower and upper bounds of the material demand time period of the material demand point respectively, as represents 0.8 times the lower bound a of the material demand time period of the material demand point, bs represents 1.2 times the upper bound b of the material demand time period of the material demand point, p1, p2 and p3 are penalty coefficients with different values, which are used to control the degree of penalty for the target transport vehicle. In actual implementation, p1, p2 and p3 can be preset through historical experiments and expert knowledge, which will not be repeated here; then, the distribution penalty window of the target material transport vehicle when transporting materials can be constructed according to the distribution penalty function, wherein the distribution penalty window is a dynamic time window used to punish the material transportation of the target material transport vehicle. In actual implementation, a dynamic time window can be set, and the distribution penalty function can be used as the penalty function of the dynamic time window, so that the distribution penalty window of the target material transport vehicle when transporting materials can be obtained.

[0078] In this embodiment, the distribution penalty coefficient corresponding to each material demand point in the transportation planning path is determined based on the distribution penalty window in the following manner, namely:

[0079] For each material demand point in the transportation planning path, extract the material demand time period of the material demand point from the material transportation demand information;

[0080] Determine the delivery time point when the target transport vehicle arrives at the material demand point;

[0081] The distribution penalty coefficient corresponding to the material demand point is determined according to the material demand time period, the distribution time point and the distribution penalty window, and then the distribution penalty coefficient corresponding to each material demand point in the transportation planning path is obtained.

[0082] In the specific implementation, first, for each material demand point in the transportation planning path, the material demand time period of the material demand point can be extracted from the material transportation demand information by traversal; then, the delivery time point of the target transport vehicle arriving at the material demand point can be determined, and the delivery time point refers to the time when the target material transport vehicle is expected to arrive at the material demand point in the transportation planning path. The delivery time point can be calculated according to factors such as the transportation speed, transportation starting point, and distance of the target material transport vehicle; finally, the delivery penalty coefficient corresponding to the material demand point can be determined based on the material demand time period, delivery time point, and delivery penalty window, wherein the delivery penalty coefficient represents the degree of penalty that the target material transport vehicle must bear when arriving at the material demand point. In actual implementation, the material demand time period and delivery time point can be input into the delivery penalty function in the delivery penalty window for calculation, so that the value of the delivery penalty function can be used as the delivery penalty coefficient corresponding to the material demand point. The delivery penalty coefficient corresponding to each material demand point in the transportation planning path can be obtained in the above manner.

[0083] It should be noted that by constructing a delivery penalty window and calculating the delivery penalty coefficient based on the delivery penalty window, the smart factory can achieve accurate scheduling and route optimization in the material transportation process. The delivery penalty window can help the system accurately set the arrival time range and penalty level of each material demand point to ensure that the material transport vehicle arrives at the target location within the appropriate time period, which avoids the situation where the material arrives early or late, thereby reducing the interference with the production plan. The calculation of the delivery penalty coefficient further helps optimize the route planning, making the delivery time of each material demand point more in line with the demand and improving the synchronization of production and material flow.

[0084] The operation path determination module 400 is used to determine the path priority of each material demand point according to the corresponding material distribution cost and the corresponding distribution penalty coefficient, and update the transportation planning path according to the path priority of each material demand point to obtain the material transportation path of the target material transport vehicle.

[0085] In this embodiment, the path priority of each material demand point can be determined according to the corresponding material delivery cost and the corresponding delivery penalty coefficient in the following manner, namely:

[0086] Determine the cost weight based on all material delivery costs;

[0087] Determine the penalty weight based on all delivery penalty coefficients;

[0088] For each material demand point in the transportation planning path, the path priority of the material demand point is determined by the cost weight, the penalty weight, the material distribution cost corresponding to the material demand point and the distribution penalty coefficient, thereby obtaining the path priority of each material demand point.

[0089] In specific implementation, first, the cost weight is determined according to all material distribution costs, wherein the cost weight is the corresponding weight of the material distribution cost. In actual implementation, the cost weight can be determined according to the following formula:

[0090]

[0091] Among them, α represents the cost weight, μ1 represents the mean of all material delivery costs, and σ1 represents the variance of all material delivery costs; then, the penalty weight can be determined according to all delivery penalty coefficients, where the penalty weight is the corresponding weight of the delivery penalty coefficient. In actual implementation, the penalty weight can be determined according to the following formula:

[0092]

[0093] Among them, β represents the penalty weight, μ2 represents the mean of all distribution penalty coefficients, and σ2 represents the variance of all distribution penalty coefficients; finally, for each material demand point in the transportation planning path, the path priority of the material demand point is determined by the cost weight, penalty weight, material distribution cost corresponding to the material demand point and distribution penalty coefficient. Among them, the path priority represents the priority of the material demand point in the path planning. In actual implementation, the path priority can be determined according to the following formula:

[0094]

[0095] Among them, γ i represents the path priority of the i-th material demand point, represents the material distribution cost corresponding to the i-th material demand point, F i represents the distribution penalty coefficient corresponding to the i-th material demand point, α represents the cost weight, and β represents the penalty weight. The path priority of each material demand point can be obtained through the above method.

[0096] In this embodiment, updating the transport planning path according to the path priority of each material demand point is to connect each material demand point in the transport planning path in descending order according to the path priority, and then obtain the material transportation path of the target material transport vehicle; it should be noted that all material demand points are sorted according to the path priority, and the path priority is arranged from high to low, and the material demand points with high priority are arranged in front, so as to connect all the material demand points to obtain the material transportation path of the target material transport vehicle. When updating the transport planning path, the material demand points are connected according to the newly sorted path priority, and the target material transport vehicle will visit each material demand point in turn according to the path priority from high to low, to ensure that the material demand points with high priority are processed first.

[0097] It should be noted that in a smart factory, by determining the path priority and updating the transportation planning path based on the material distribution cost and distribution penalty coefficient, not only can the distribution path of the material transport vehicle be planned efficiently, but also the material transportation efficiency can be improved and costs can be reduced.

[0098] It can be seen that in this application, firstly, by accurately calculating and optimizing the material distribution cost, it can ensure that the material transport vehicle completes the task in the shortest and most energy-efficient way, thereby reducing the overall transportation time; then, by constructing a distribution penalty window and calculating the distribution penalty coefficient based on the distribution penalty window, the smart factory can achieve accurate scheduling and path optimization in the material transportation process. The distribution penalty window can help the system accurately set the arrival time range and penalty degree of each material demand point, ensure that the material transport vehicle arrives at the target location within the appropriate time period, and the calculation of the distribution penalty coefficient further helps to optimize the path planning; finally, in the smart factory, by determining the path priority and updating the transportation planning path according to the material distribution cost and the distribution penalty coefficient, not only can the distribution path of the material transport vehicle be efficiently planned, but also the material transportation efficiency can be improved and the cost can be reduced.

[0099] In summary, the technical solution adopted in this application can efficiently plan the distribution routes of material transport vehicles when distributing materials in smart factories.

[0100] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0101] Those skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0102] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. An intelligent material transportation control system for a smart factory, characterized in that: The control system comprises: A demand acquisition module is used to obtain material transportation demand information in the smart factory, and extract all material demand points corresponding to the target material transport vehicle from the material transportation demand information; A path planning module is used to obtain the transportation parameters of the target material transport vehicle, determine the material distribution cost between the target material transport vehicle and each material demand point according to the transportation parameters, and construct the transportation planning path of the target material transport vehicle according to all the material distribution costs; A distribution penalty module is used to construct a distribution penalty window for a target material transport vehicle when transporting materials, and determine a distribution penalty coefficient corresponding to each material demand point in the transportation planning path based on the distribution penalty window; The operation path determination module is used to determine the path priority of each material demand point according to the corresponding material distribution cost and the corresponding distribution penalty coefficient, and update the transportation planning path according to the path priority of each material demand point to obtain the material transportation path of the target material transport vehicle.

2. The intelligent material transportation control system of a smart factory as claimed in claim 1, characterized in that: Obtain material transportation demand information in the smart factory from the production planning system of the smart factory.

3. The intelligent material transportation control system of a smart factory as claimed in claim 1, characterized in that: Extracting all material demand points corresponding to the target material transport vehicle from the material transport demand information specifically includes: Get the unique ID of the target material transport vehicle; Determine the transport responsible block of the target material transport vehicle in the smart factory according to the unique identifier; Extracting all material demand points within the transport responsible area from the material transport demand information; All material demand points within the transport responsible area are regarded as all material demand points corresponding to the target material transport vehicle.

4. The intelligent material transportation control system of a smart factory as claimed in claim 1, characterized in that: The transportation parameters of the target material transport vehicle are obtained through the intelligent sensor network.

5. The intelligent material transportation control system of a smart factory as claimed in claim 1, characterized in that: Determining the material distribution cost between the target material transport vehicle and each material demand point based on the transportation parameters specifically includes: Extracting the transport speed, transport starting point and transport load of the target material transport vehicle from the transport parameters; For each material demand point, obtain the location information of the material demand point; Determine the transportation distance cost between the target material transport vehicle and the material demand point according to the transportation starting point and the location information; Determine the transportation time cost between the target material transport vehicle and the material demand point by using the transportation speed and the transportation distance cost; The transportation energy consumption cost between the target material transport vehicle and the material demand point is determined based on the transportation load and the transportation distance cost: The material distribution cost between the target material transport vehicle and the material demand point is determined according to the transport distance cost, the transport time cost and the transport energy consumption cost, and then the material distribution cost between the target material transport vehicle and each material demand point is obtained.

6. The intelligent material transportation control system of a smart factory as claimed in claim 1, characterized in that: Constructing the transportation planning path of the target material transport vehicle based on all material distribution costs is to connect all material demand points in ascending order according to the material distribution costs, and then obtain the transportation planning path of the target material transport vehicle.

7. The intelligent material transportation control system of a smart factory as claimed in claim 1, characterized in that: Constructing the delivery penalty window of the target material transport vehicle when transporting materials specifically includes: Construct a distribution penalty function for the target material transport vehicle when transporting materials; A delivery penalty window is constructed for the target material transport vehicle when transporting materials according to the delivery penalty function.

8. The intelligent material transportation control system of a smart factory as claimed in claim 1, characterized in that: Determining the distribution penalty coefficient corresponding to each material demand point in the transportation planning path based on the distribution penalty window specifically includes: For each material demand point in the transportation planning path, extract the material demand time period of the material demand point from the material transportation demand information; Determine the delivery time point when the target transport vehicle arrives at the material demand point; The distribution penalty coefficient corresponding to the material demand point is determined according to the material demand time period, the distribution time point and the distribution penalty window, and then the distribution penalty coefficient corresponding to each material demand point in the transportation planning path is obtained.

9. The intelligent material transportation control system of a smart factory as claimed in claim 1, characterized in that: The path priority of each material demand point is determined based on the corresponding material distribution cost and the corresponding distribution penalty coefficient, including: Determine the cost weight based on all material delivery costs; Determine the penalty weight based on all delivery penalty coefficients; For each material demand point in the transportation planning path, the path priority of the material demand point is determined by the cost weight, the penalty weight, the material distribution cost corresponding to the material demand point and the distribution penalty coefficient, thereby obtaining the path priority of each material demand point.

10. The intelligent material transportation control system of a smart factory as claimed in claim 1, characterized in that: Updating the transport planning path according to the path priority of each material demand point is to connect each material demand point in the transport planning path in descending order according to the path priority, and then obtain the material transportation path of the target material transport vehicle.

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