New energy automobile production part supply control system, method and device

Abstract

The application discloses a new energy automobile production part supply control system, method and device, which comprises the following steps: collecting original data, including supplier basic data, regional distribution center basic data, factory data, process data and truck data; data processing, regularly purchasing parts, and according to the supplier and factory distribution, regional distribution center basic data, part type and quantity, truck data and process information, the walking route, carrying information and time information of the truck, the pickup time information and logistics information of the intersection; the factory production management department indicates the working state of the logistics supplier according to the data processing result, indicates the working state of the intersection according to the pickup time information of the intersection, and indicates the supply state of each supplier and the temporary storage state of each regional distribution center according to the logistics information.

Description

Supply control system, method and device for new energy vehicle manufacturing components Technical Field

[0001] This invention belongs to the field of new energy vehicle technology, and in particular relates to a supply management system, method and device for new energy vehicle production components. Background Technology

[0002] The automotive industry has a long history of development, especially in recent years with the rapid growth of new energy vehicles, which has driven a demand for transformation across the entire industry. The automotive industry is a complex combination of multiple operating conditions, and the supply of automotive parts during the production stage plays a crucial role in the overall supply chain. Currently, most mainstream automotive OEMs adopt a cyclical pickup logistics system as their preferred solution for automotive parts supply during the production stage. Cyclic pickup standardizes operations, ensuring on-time and even delivery, thus guaranteeing timely supply for even production. It also reduces transportation costs, increases truck utilization, and minimizes transportation waste; furthermore, it lowers inventory costs by using small batches and multiple shipments to reduce factory inventory. The implementation of cyclical pickup relies on a parts supply plan that is highly planned, feasible, evenly distributed, accurate, and adaptable.

[0003] As is well known, in the new energy vehicle industry, due to the large number of parts and components, in order to improve production efficiency, the parts and components of new energy vehicles are designed, manufactured and processed by different companies in different regions. Then, the finished parts and components are transported to the new energy vehicle assembly base for assembly and debugging using logistics.

[0004] Currently, to ensure the normal and orderly operation of new energy vehicle assembly bases, a large number of professional staff are needed to coordinate and manage the supply volume, supply rate, and demand of spare parts within the assembly base. During this coordination and management process, a delay in any information can trigger a series of chain reactions. Therefore, in summary, the required technology has the following shortcomings:

[0005] First, to ensure the timeliness and comprehensiveness of information, a large number of staff are needed; with the continuous expansion of the new energy vehicle industry, traditional manual methods are difficult to meet the needs of large-scale intelligent production.

[0006] Second, poor adaptability; when an error occurs in one part of the process, it is difficult for other staff to take timely and comprehensive remedial measures.

[0007] Third, as the number of staff continues to increase, the large amount of data collection and processing requires staff to screen and process it, which can easily lead to errors.

[0008] Fourth, the efficiency is relatively low. Summary of the Invention

[0009] In view of the problems existing in the prior art, the purpose of this invention is to provide a supply management and control system, method and device for new energy vehicle production components. This supply management and control system, method and device for new energy vehicle production components utilizes big data, Internet and computer for data processing, and coordinates and manages multiple links according to the structure of data processing to ensure the normal operation of the entire supply chain.

[0010] One objective of this invention is to provide a component supply management system for new energy vehicle production, comprising at least:

[0011] S1. Collect raw data, including supplier basic data, regional distribution center basic data, factory data, process data, and truck data. The supplier basic data includes the location information of each supplier, distance information between adjacent suppliers, distance information from each supplier to the regional distribution center, distance information from each supplier to the factory, and parts supply information for each supplier. The regional distribution center basic data includes the location information of each regional distribution center and information on temporarily stored parts within that center. The factory data includes the location information of each factory, process information for each factory, gate information for each factory, and attendance calendar and time information for each factory. The process data includes the time data and specific process sequence for each process. The truck data includes the vehicle model data and status data for each truck.

[0012] S2. Data processing: Regularly purchase the required quantity and type of parts from parts suppliers, and formulate the following information based on factory distribution, basic data of regional distribution centers, types and quantities of parts, truck data and process information: truck travel routes, loading information and time information, cargo pick-up and drop-off time information at checkpoints and logistics information.

[0013] S3. Based on the data processing results, the factory production management department instructs the logistics supplier's work status according to the truck's travel route and time information, instructs the level crossing's work status according to the level crossing's cargo pickup time information, and instructs the supply status of each supplier and the temporary storage status of each regional distribution center according to the logistics information.

[0014] Further: The loading information includes the cargo volume and the volume of each component; the cargo volume is greater than the sum of the volumes of each component.

[0015] Furthermore, during data processing, if a vehicle experiences an anomaly en route, an accident occurs in a process, or a factory production malfunctions, the truck's route, cargo loading and unloading information, the pick-up and drop-off times at the checkpoint, and logistics information need to be adjusted accordingly based on the fault information.

[0016] Further: The above-mentioned truck's route is a cyclical pickup route. Specifically, based on the principle of small batches and high frequency, multiple suppliers that need to pick up goods in a region are sequentially linked to form one or more optimal pickup chains. Then, the truck departs from the factory, picks up goods from each supplier in turn, and finally returns to the factory gate.

[0017] Further: The aforementioned truck's route is a cyclical pickup route, specifically: based on the principle of small batches and high frequency, multiple suppliers requiring pickup within a region are sequentially linked to form one or more optimal pickup chains. Subsequently, the truck departs from the regional distribution center to pick up goods from each supplier in turn, returns to the regional distribution center to temporarily store the parts there; finally, the truck departs from the regional distribution center to deliver the parts from the regional distribution center to the factory entrance.

[0018] The second objective of this invention is to provide a component supply management and control system for new energy vehicle production, comprising at least:

[0019] Data Acquisition Module: Collects raw data, including supplier basic data, regional distribution center basic data, factory data, process data, and truck data. Supplier basic data includes the location information of each supplier, distance information between adjacent suppliers, distance information from each supplier to the regional distribution center, distance information from each supplier to the factory, and parts supply information for each supplier. Regional distribution center basic data includes the location information of each regional distribution center and information on temporarily stored parts within that center. Factory data includes the location information of each factory, process information for each factory, gate information for each factory, and attendance calendar and time information for each factory. Process data includes the time data and specific process sequence for each process. Truck data includes the vehicle type and status data for each truck.

[0020] Data processing module: Regularly purchases the required quantity and type of parts from parts suppliers, and formulates the following information based on factory distribution, basic data of regional distribution centers, types and quantities of parts, truck data and process information: truck travel routes, loading information and time information, cargo pick-up and drop-off time information at checkpoints and logistics information.

[0021] The output execution module, based on the data processing results, instructs the logistics supplier's work status according to the truck's travel route and time information, instructs the level crossing's work status according to the level crossing's cargo pickup time information, and instructs each supplier's supply status and each regional distribution center's temporary storage status according to the logistics information.

[0022] The third objective of this invention is to provide a computer program for implementing the above-mentioned method for controlling the supply of components used in the production of new energy vehicles.

[0023] The fourth objective of this invention is to provide an information data processing terminal for implementing the above-mentioned method for controlling the supply of components for new energy vehicle production.

[0024] The fifth objective of this invention is to provide a computer-readable storage medium, including instructions that, when executed on a computer, cause the computer to perform the aforementioned method for controlling the supply of components for the production of new energy vehicles.

[0025] The sixth objective of this invention is to provide a device that applies the above-mentioned supply control system for new energy vehicle production components.

[0026] The advantages and positive effects of this invention are as follows:

[0027] By adopting the above technical solution, the present invention has the following technical effects:

[0028] This patent utilizes computer internet and big data technologies to replace traditional manual data collection, aggregation, and processing; it greatly improves work efficiency, ensures data timeliness, and achieves unified data management; it guarantees the normal, efficient, and rational operation of the entire supply chain; at the same time, it avoids human error and improves the timeliness, reliability, and rationality of data. This ensures the security of the entire supply chain. Attached Figure Description

[0029] Figure 1 is a flowchart of the loading time in a preferred embodiment of the present invention;

[0030] Figure 2 is a first flowchart of the crossing time in a preferred embodiment of the present invention;

[0031] Figure 3 is a second flowchart of the crossing time in a preferred embodiment of the present invention;

[0032] Figure 4 is a first flowchart of the route timing in a preferred embodiment of the present invention;

[0033] Figure 5 is a second flowchart of the route timing in a preferred embodiment of the present invention;

[0034] Figure 6 is a first flowchart of the logistics planning time in a preferred embodiment of the present invention;

[0035] Figure 7 is a second flowchart of the logistics planning time in a preferred embodiment of the present invention;

[0036] Figure 8 is a third flowchart of the logistics planning time in a preferred embodiment of the present invention;

[0037] Figure 9 is a fourth flowchart of the logistics planning time in a preferred embodiment of the present invention; Detailed Implementation

[0038] To further understand the invention's content, features, and effects, the following embodiments are provided, and detailed descriptions are given in conjunction with the accompanying drawings.

[0039] The structure of the present invention will now be described in detail with reference to the accompanying drawings.

[0040] The main components of new energy vehicles differ from those of traditional fuel vehicles. Therefore, the management of the supply chain for new energy components must differ from that of the traditional automotive industry. Higher requirements are placed on timeliness, responsiveness, quality, and risk control. To match these high-demand supply capabilities, more precise supply instructions are needed, emphasizing planning, feasibility, standardization, accuracy, and responsiveness. However, higher precision in supply instructions requires more complex data processing and computation, leading to higher manpower and physical resource costs. Therefore, designing and developing a time-saving, efficient, and labor-saving supply management system, method, and processing terminal that can monitor automotive component supply orders in real time, provide more precise component supply instructions based on production plans, and promptly update order requirements and supply plans as needed, while also tracking order status throughout the entire process, is of paramount importance.

[0041] A method for supply control of components used in the production of new energy vehicles, comprising:

[0042] S1. Collect raw data, including supplier basic data, regional distribution center basic data, factory data, process data, and truck data. The supplier basic data includes the location information of each supplier, distance information between adjacent suppliers, distance information from each supplier to the regional distribution center, distance information from each supplier to the factory, and parts supply information for each supplier. The regional distribution center basic data includes the location information of each regional distribution center and information on temporarily stored parts within that center. The factory data includes the location information of each factory, process information for each factory, gate information for each factory, and attendance calendar and time information for each factory. The process data includes the time data and specific process sequence for each process. The truck data includes the vehicle model data and status data for each truck.

[0043] S2. Data processing: Regularly purchase the required quantity and type of parts from parts suppliers, and formulate the following information based on factory distribution, basic data of regional distribution centers, types and quantities of parts, truck data and process information: truck travel routes, loading information and time information, cargo pick-up and drop-off time information at checkpoints and logistics information.

[0044] S3. Based on the data processing results, the factory production management department instructs the logistics supplier's work status according to the truck's travel route and time information, instructs the level crossing's work status according to the level crossing's cargo pickup time information, and instructs the supply status of each supplier and the temporary storage status of each regional distribution center according to the logistics information.

[0045] Preferably, the loading information includes the cargo volume and the volume of each component; the cargo volume is greater than the sum of the volumes of each component.

[0046] As a preferred approach: during data processing, if a vehicle experiences an anomaly en route, an accident occurs in the process, or a line malfunctions, the truck's route, cargo loading and unloading information, the pick-up and drop-off time at the crossing, and logistics information need to be adjusted accordingly based on the fault information.

[0047] As a preferred option, the above-mentioned trucks travel on a circular pickup route. Specifically, based on the principle of small batches and high frequency, multiple suppliers that need to pick up goods in a region are sequentially linked to form one or more optimal pickup chains. Then, the trucks depart from the factory, pick up goods from each supplier in turn, and finally return to the factory gate.

[0048] As a preferred option, the above-mentioned truck travels on a circular pickup route. Specifically, based on the principle of small batches and high frequency, multiple suppliers that need to be picked up are sequentially linked to form one or more optimal pickup chains. Then, the truck departs from the regional distribution center to pick up goods from each supplier in turn, returns to the regional distribution center to temporarily store the parts, and finally departs from the regional distribution center to deliver the parts from the regional distribution center to the factory entrance.

[0049] A component supply management and control system for new energy vehicle production includes:

[0050] Data Acquisition Module: Collects raw data, including supplier basic data, regional distribution center basic data, factory data, process data, and truck data. The supplier basic data includes the location information of each supplier, distance information between adjacent suppliers, distance information from each supplier to the regional distribution center, and parts supply information for each supplier. The regional distribution center basic data includes the location information of each regional distribution center and information on temporarily stored parts within that center. The factory data includes the location information of each factory, process information for each factory, gate information for each factory, and attendance calendar and time information for each factory. The process data includes the time data and specific process sequence for each process. The truck data includes the vehicle type and status data for each truck.

[0051] Data processing module: Regularly purchases the required quantity and type of parts from parts suppliers, and formulates the following information based on factory distribution, basic data of regional distribution centers, types and quantities of parts, truck data and process information: truck travel routes, loading information and time information, cargo pick-up and drop-off time information at checkpoints and logistics information.

[0052] The output execution module, based on the data processing results, instructs the logistics supplier's working status according to the truck's travel route and time information, instructs the level crossing's working status according to the level crossing's cargo pickup time information, and instructs the supply status of each supplier and the temporary storage status of each regional distribution center according to the logistics information.

[0053] A computer program for a method of controlling the supply of components used in the production of new energy vehicles, the method comprising:

[0054] S1. Collect raw data, including supplier basic data, regional distribution center basic data, factory data, process data, and truck data. The supplier basic data includes the location information of each supplier, distance information between adjacent suppliers, distance information from each supplier to the regional distribution center, and parts supply information for each supplier. The regional distribution center basic data includes the location information of each regional distribution center and information on temporarily stored parts within that center. The factory data includes the location information of each factory, process information for each factory, gate information for each factory, and attendance calendar and time information for each factory. The process data includes the time data and specific process sequence for each process. The truck data includes the vehicle model data and status data for each truck.

[0055] S2. Data processing: Regularly purchase a certain quantity and type of parts required by the factory from parts suppliers, and formulate the following information based on the factory distribution, basic data of regional distribution centers, types and quantities of parts, truck data and process information: truck travel routes, loading information and time information, cargo pick-up and drop-off time information at checkpoints and logistics information.

[0056] S3. Based on the data processing results, the factory production management department instructs the logistics supplier's work status according to the truck's travel route and time information, instructs the level crossing's work status according to the level crossing's cargo pickup time information, and instructs the supply status of each supplier and the temporary storage status of each regional distribution center according to the logistics information.

[0057] Preferably, the loading information includes the cargo volume and the volume of each component; the cargo volume is greater than the sum of the volumes of each component.

[0058] As a preferred approach: during data processing, if a vehicle experiences an anomaly en route, an accident occurs in the process, or a factory production malfunctions, the truck's route, cargo loading and unloading information, the pick-up and drop-off time at the checkpoint, and logistics information need to be adjusted accordingly based on the fault information.

[0059] As a preferred option, the above-mentioned truck's route is a cyclical pickup route. Specifically, based on the principle of small batches and high frequency, multiple suppliers that need to be picked up are sequentially linked to form one or more optimal pickup chains. Then, the truck departs from the factory, picks up goods from each supplier in turn, and finally returns to the factory gate.

[0060] As a preferred option, the aforementioned truck's travel route is a cyclical pickup route. Specifically, based on the principle of small batches and high frequency, multiple suppliers that need to be picked up are sequentially linked to form one or more optimal pickup chains. Then, the truck departs from the regional distribution center to pick up goods from each supplier in turn, returns to the regional distribution center to temporarily store the parts there, and finally departs from the regional distribution center to deliver the parts from the regional distribution center to the factory entrance.

[0061] An information data processing terminal for implementing a method for controlling the supply of components used in the production of new energy vehicles, the method comprising:

[0062] S1. Collect raw data, including supplier basic data, regional distribution center basic data, factory data, process data, and truck data. The supplier basic data includes the location information of each supplier, distance information between adjacent suppliers, distance information from each supplier to the regional distribution center, distance information from each supplier to the factory, and parts supply information for each supplier. The regional distribution center basic data includes the location information of each regional distribution center and information on temporarily stored parts within that center. The factory data includes the location information of each factory, process information for each factory, gate information for each factory, and attendance calendar and time information for each factory. The process data includes the time data and specific process sequence for each process. The truck data includes the vehicle model data and status data for each truck.

[0063] S2. Data processing: Regularly purchase the required quantity and type of parts from parts suppliers, and formulate the following information based on factory distribution, basic data of regional distribution centers, types and quantities of parts, truck data and process information: truck travel routes, loading information and time information, cargo pick-up and drop-off time information at checkpoints and logistics information.

[0064] S3. Based on the data processing results, the factory production management department instructs the logistics supplier's work status according to the truck's travel route and time information, instructs the level crossing's work status according to the level crossing's cargo pickup time information, and instructs the supply status of each supplier and the temporary storage status of each regional distribution center according to the logistics information.

[0065] Preferably, the loading information includes the cargo volume and the volume of each component; the cargo volume is greater than the sum of the volumes of each component.

[0066] As a preferred approach: during data processing, if a vehicle experiences an anomaly en route, an accident occurs in the process, or a factory production malfunctions, the truck's route, cargo loading and unloading information, the pick-up and drop-off time at the checkpoint, and logistics information need to be adjusted accordingly based on the fault information.

[0067] As a preferred option, the above-mentioned truck's route is a cyclical pickup route. Specifically, based on the principle of small batches and high frequency, multiple suppliers that need to be picked up are sequentially linked to form one or more optimal pickup chains. Then, the truck departs from the factory, picks up goods from each supplier in turn, and finally returns to the factory gate.

[0068] As a preferred option, the aforementioned truck's route is a cyclical pickup route, specifically: following the principle of small batches and high frequency, multiple suppliers requiring pickup are sequentially linked to form one or more optimal pickup chains. Subsequently, the truck departs from the regional distribution center to pick up goods from each supplier in turn, returns to the regional distribution center to temporarily store the parts there, and finally departs from the regional distribution center to deliver the parts from the regional distribution center to the factory entrance.

[0069] A computer-readable storage medium includes instructions that, when executed on a computer, cause the computer to perform a method for controlling the supply of components for the production of new energy vehicles, the method comprising:

[0070] S1. Collect raw data, including supplier basic data, regional distribution center basic data, factory data, process data, and truck data. The supplier basic data includes the location information of each supplier, distance information between adjacent suppliers, distance information from each supplier to the regional distribution center, distance information from each supplier to the factory, and parts supply information for each supplier. The regional distribution center basic data includes the location information of each regional distribution center and information on temporarily stored parts within that center. The factory data includes the location information of each factory, process information for each factory, gate information for each factory, and attendance calendar and time information for each factory. The process data includes the time data and specific process sequence for each process. The truck data includes the vehicle model data and status data for each truck.

[0071] S2. Data processing: Regularly purchase the required quantity and type of parts from parts suppliers, and formulate the following information based on factory distribution, basic data of regional distribution centers, types and quantities of parts, truck data and process information: truck travel routes, loading information and time information, cargo pick-up and drop-off time information at checkpoints and logistics information.

[0072] S3. Based on the data processing results, the factory production management department instructs the logistics supplier's work status according to the truck's travel route and time information, instructs the level crossing's work status according to the level crossing's cargo pickup time information, and instructs the supply status of each supplier and the temporary storage status of each regional distribution center according to the logistics information.

[0073] Preferably, the loading information includes the cargo volume and the volume of each component; the cargo volume is greater than the sum of the volumes of each component.

[0074] As a preferred approach: during data processing, if a vehicle experiences an anomaly en route, an accident occurs in the process, or a factory production malfunctions, the truck's route, cargo loading and unloading information, the pick-up and drop-off time at the checkpoint, and logistics information need to be adjusted accordingly based on the fault information.

[0075] As a preferred option, the above-mentioned truck's travel route is a cyclical pickup route. Specifically, based on the principle of small batches and high frequency, multiple suppliers that need to be picked up are sequentially linked to form one or more optimal pickup chains. Then, the truck departs from the factory, picks up goods from each supplier in turn, and finally returns to the factory gate.

[0076] As a preferred option, the aforementioned truck's route is a cyclical pickup route, specifically: following the principle of small batches and high frequency, multiple suppliers requiring pickup are sequentially linked to form one or more optimal pickup chains. Subsequently, the truck departs from the regional distribution center to pick up goods from each supplier in turn, returns to the regional distribution center to temporarily store the parts there, and finally departs from the regional distribution center to deliver the parts from the regional distribution center to the factory entrance.

[0077] A device for controlling the supply of components used in the production of new energy vehicles, wherein the method for controlling the supply of components used in the production of new energy vehicles includes:

[0078] S1. Collect raw data, including supplier basic data, regional distribution center basic data, factory data, process data, and truck data. The supplier basic data includes the location information of each supplier, distance information between adjacent suppliers, distance information from each supplier to the regional distribution center, distance information from each supplier to the factory, and parts supply information for each supplier. The regional distribution center basic data includes the location information of each regional distribution center and information on temporarily stored parts within that center. The factory data includes the location information of each factory, process information for each factory, gate information for each factory, and attendance calendar and time information for each factory. The process data includes the time data and specific process sequence for each process. The truck data includes the vehicle model data and status data for each truck.

[0079] S2. Data processing: Regularly purchase the required quantity and type of parts from parts suppliers, and formulate the following information based on factory distribution, basic data of regional distribution centers, types and quantities of parts, truck data and process information: truck travel routes, loading information and time information, cargo pick-up and drop-off time information at checkpoints and logistics information.

[0080] S3. Based on the data processing results, the factory production management department instructs the logistics supplier's work status according to the truck's travel route and time information, instructs the level crossing's work status according to the level crossing's cargo pickup time information, and instructs the supply status of each supplier and the temporary storage status of each regional distribution center according to the logistics information.

[0081] Preferably, the loading information includes the cargo volume and the volume of each component; the cargo volume is greater than the sum of the volumes of each component.

[0082] As a preferred approach: during data processing, if a vehicle experiences an anomaly en route, an accident occurs in the process, or a factory production malfunctions, the truck's route, cargo loading and unloading information, the pick-up and drop-off time at the checkpoint, and logistics information need to be adjusted accordingly based on the fault information.

[0083] As a preferred option, the above-mentioned truck's route is a cyclical pickup route. Specifically, based on the principle of small batches and high frequency, multiple suppliers that need to be picked up are sequentially linked to form one or more optimal pickup chains. Then, the truck departs from the factory, picks up goods from each supplier in turn, and finally returns to the factory gate.

[0084] As a preferred option, the aforementioned truck's route is a cyclical pickup route. Specifically, based on the principle of small batches and high frequency, multiple suppliers that need to be picked up are sequentially linked to form one or more optimal pickup chains. Then, the truck departs from the regional distribution center to pick up goods from each supplier in turn, returns to the regional distribution center to temporarily store the parts, and finally departs from the regional distribution center to deliver the parts from the regional distribution center to the factory entrance.

[0085] A component supply control device for new energy vehicle production, comprising:

[0086] The mobile operating terminal is used to scan part labels, read and verify part information, and upload relevant data.

[0087] Data terminals are used to store component information, supplier information, and factory-related information.

[0088] The network control terminal is used for human-machine interaction; specifically, it verifies the operator's operating permissions through the login window, reads some data from the data terminal according to the operating permissions, writes basic data to the data terminal according to the operating permissions, maintains and generates high-precision production component supply instructions, including component-level logistics instructions, route time instructions, and factory gate time instructions.

[0089] The network management terminal interacts with the data terminal and the mobile operation terminal respectively.

[0090] Working Principle: Before use, the above technical solution involves a data interface to write or modify basic data from other relevant systems to the data terminal. During use, the network management terminal first selects a production plan and parts order information for a specific period. Then, through route planning, material loading schedules, and gate adjustments, it generates parts-level logistics instructions, route timetables, and factory gate timetables. Subsequently, these instructions are transmitted to the order management system via the data interface. The order management system user generates documents and parts information tags based on these instructions. The network management terminal receives the documents and parts information tags and pushes the content, along with the instructions generated by the network management terminal, to the mobile operating terminal. The mobile operating terminal user scans and identifies the physical objects, sending the order information to the data terminal in real time. Throughout this process, staff can perform simple route planning, material loading schedules, and gate adjustments using the network management terminal. After system processing, high-precision parts supply plans are obtained. The network management terminal tracks the entire parts order status by receiving scans from the mobile operating terminal and transmitting order status updates in real time. Clearly, this technical solution is time-saving, efficient, and saves manpower. It can also monitor automotive parts supply order information in real time and provide more accurate parts supply plans based on production plans. Furthermore, it allows for timely changes to order requirements and parts supply plans by specifying the logistics plan period, and enables full tracking of order status.

[0091] Please refer to Figure 1.

[0092] Explanation of the name:

[0093] RDC: Regional Distribution Center; Time unit m is minutes;

[0094] The steps for generating route timetable information are as follows:

[0095] S1. Sequentially obtain: original unit information of work time, walking data information, and route information; among which:

[0096] The original unit information for work time mainly includes the unit work time information for each process;

[0097] The walking data information mainly includes the location information of each stop, the distance information between stops, and the working time information of each stop;

[0098] The route information mainly includes supplier information for the planned route and information on the number of times the route has been used.

[0099] S2. Obtain route and passenger information; specifically:

[0100] S201. Obtain cargo loading information;

[0101] S202, Entering the route, the information on each vehicle is repeatedly calculated and identified; specifically, it is divided into the following three cases:

[0102] If the next loading route is from the supplier to the regional distribution center, then calculate the volume of the pickup station, that is, calculate the total volume of the supplier stations; the next step is to calculate the volume of the destination station, that is, the total volume of the supplier stations entering the regional distribution center.

[0103] If the next loading route is from the regional distribution center to the factory, calculate the volume of the pickup station, which is the total volume of the supplier stations entering the regional distribution center. The next step is to calculate the volume of the destination station, which is to calculate the total volume according to the gate.

[0104] If the next loading route is from the supplier to the factory, calculate the volume of the pickup station, that is, calculate the total volume according to the supplier's station. The next step is to calculate the volume of the destination station, that is, calculate the total volume according to the crossing.

[0105] Once the information on the different types of routes is obtained, the loop calculation ends.

[0106] S3. Obtain the regional distribution center gate allocation information for the route from the supplier to the regional distribution center;

[0107] S4. Calculate the required operation time for each station based on the route and boarding information; the required operation time is the sum of the operation time of each process and the travel time.

[0108] S5. Calculate the travel time to the next station based on the travel information, and write the calculation result into the route timetable database.

[0109] Please refer to Figure 2.

[0110] Step A for calculating the crossing time is as follows:

[0111] S1. Sequentially retrieve the attendance calendar, work time and original unit information, travel data information, and route information, including:

[0112] The attendance calendar shows the factory's attendance dates for the entire year.

[0113] The original unit information for work time mainly includes the unit work time information for each process;

[0114] The walking data information mainly includes the location information of each stop, the distance information between stops, and the working time information of each stop;

[0115] The route information mainly includes the route name and the number of times the route has been run.

[0116] S2. Obtain route trips. Specifically, calculate the order list of pickup stations and the order list of level crossings for each route, the previous trip of the same vehicle, and identify whether this route trip goes to multiple level crossings.

[0117] S3, route and pick-up information;

[0118] Obtain freight volume information for each station on the route using the same method as generating the route timetable information mentioned earlier.

[0119] S4. Obtain a list of level crossings.

[0120] Specifically, based on the list of level crossings and the timetable for level crossings on the base date, the order of entry and exit at each level crossing is obtained.

[0121] Please refer to Figure 3.

[0122] The specific steps for calculating the crossing time B are as follows:

[0123] S1. Obtain the factory calendar information, i.e., the factory's attendance dates for the whole year;

[0124] S2. Create a starting task - the starting time is the factory's working hours;

[0125] S3. Create a completed task - start time is the factory's closing time;

[0126] S4. Based on the route sequence in the level crossing overview, create loading and unloading tasks and add priority relationships;

[0127] For S5 routes with multiple crossings, create transportation tasks (between crossings) according to the order of the crossings and add the sequence relationship;

[0128] S6. For vehicles with multiple trips, after the second trip, a transportation (pickup) task is added, and a priority relationship is added (the last checkpoint of the previous trip takes priority over transportation, which takes priority over the first checkpoint of the subsequent trip).

[0129] S7. Starting from the initial task, calculate the start and end times of each subsequent task based on their sequence. (Break times should be considered during the calculation; tasks should be tightly scheduled without gaps.)

[0130] S8. Check if it is past the end of the workday.

[0131] If a timeout occurs, an exception is thrown. (After the exception is caught on the outside, the calculation result is still written to the level crossing timetable, and the reason for the exception is written to the background exception summary). An attempt is made to adjust the interval between trips; that is, for trips with multiple trips per day, try to make them arrive at more even time intervals. (Since the previous schedule was tightly packed without any gaps, if the trip exceeds the end of the workday, it means there is no way to schedule it, and no adjustment is needed.) The exception is resolved, and the result is written to the level crossing timetable.

[0132] If it does not exceed the time limit.

[0133] S801. A list of level crossings to be adjusted needs to be constructed, which only includes level crossings with multiple routes (level crossings without multiple routes do not need to be adjusted). Among them, simple level crossings (without multiple routes) are given priority, followed by level crossings with multiple routes.

[0134] S802 cycle: Adjustment attempt at the level crossing to be adjusted.

[0135] S80201. First, save the state before adjustment.

[0136] The interval between urination sessions is calculated as follows: Interval between urination sessions = (Working time from the first urination session until the end of the workday at the checkpoint - Total working time at the checkpoint throughout the day - Loading and unloading time per session * Number of urination sessions) / Number of urination sessions;

[0137] S80202, Add an adjustment task that reduces the number of times by 1, and link it to each loading and unloading task. Starting from the initial task, calculate the start and end times of each subsequent task based on their sequence.

[0138] S80203. Verification: If an error occurs, revert to the state before adjustment, i.e., S80201. Finally, update the level crossing timetable, that is, write the calculation results during the process into the level crossing timetable.

[0139] Please refer to Figure 4.

[0140] The specific steps for calculating route time A are as follows:

[0141] Explanation of the name:

[0142] RDC: Regional Distribution Center; SP: Parts Supplier; ID: Identification Code;

[0143] S1. Sequentially obtain: attendance calendar, work time and original unit information, walking data information, and route information; among which:

[0144] The original unit information for work time mainly includes the unit work time information for each process;

[0145] The walking data information mainly includes the location information of each stop, the distance information between stops, and the working time information of each stop;

[0146] The route information mainly includes supplier information for the planned route and the number of times the route has been run; the supplier information mainly includes supplier name, supplier code, and supplier-supplied parts information.

[0147] S2. Obtain the supplier inventory time for each route from SP to RDC;

[0148] S201. Obtain cargo loading information, including: route, number of trips, origin, destination, route type, supplier, volume, etc. (The method for obtaining route and number of trips loading information is the same as that used in calculating crossing timetables.)

[0149] S202. Traverse the cargo loading information, process only the SP-RDC route, and find the route with the longest inventory time among all suppliers.

[0150] S3. Route timetable information: Retrieve the route timetable calculated in the previous route timetable generation process (at this point, only the cargo volume, station sequence, and travel time are available; the timetable has not yet been calculated).

[0151] S4. Obtain route information. Specifically, calculate the order list of pickup stations and the order list of level crossings for each route, the previous trip of the same vehicle, and identify whether this route trip goes to multiple level crossings.

[0152] S5. Obtain route timetable loading information and freight volume information for each station on the route timetable, using the same method as generating the route timetable loading information.

[0153] S6. Level Crossing Overview: Specifically, based on the Level Crossing Overview Table and Level Crossing Timetable of the reference date, obtain the order of entry and exit at each level crossing.

[0154] Please refer to Figure 5. The specific steps for calculating route time B are as follows:

[0155] S1. Obtain the correspondence between the number of routes from RDC to the factory and the number of routes from SP to RDC. Specifically, first query the logistics instruction number table sorted by the route planning object ID, which is better than the logistics instruction number, which is better than the route type. Then iterate through the table and construct the correspondence between the number of routes from RDC to the factory and the number of routes from SP to the factory for each route planning object ID and logistics instruction number.

[0156] S2. Calculate the crossing time. Specifically, use the same logic as calculating the crossing time to construct the task. However, the time stamp of the crossing loading and unloading task is locked. Calculate the crossing time and simultaneously check whether the locked state is satisfied. At this time, there is no need to perform multiple crossing equalization.

[0157] S3. Reflect the crossing times onto the route times, and supplement the previously obtained route times with the crossing times.

[0158] S4. Traverse the route to the factory.

[0159] If the value is empty, execute S5 directly.

[0160] If the value is not empty, proceed to the next step.

[0161] S0401. Obtain the start time of the first level crossing and work backwards to calculate the transportation and loading / unloading times at each cargo collection station.

[0162] S0402. If it is a [RDC-Factory] route, calculate the corresponding [Supplier-RDC] route number for the [RDC-Factory] route number; S0403. Traverse the corresponding [Supplier-RDC] route numbers.

[0163] If the value is empty, execute S5 directly.

[0164] If the value is not empty, proceed to the next step. Starting with the pickup time of [RDC-Factory] plus the dwell time, work backwards to calculate the transportation and loading / unloading time of each pickup station along the [Supplier-RDC] route.

[0165] S5, Update route timetable

[0166] S6. Update the RDC gate timetable in the level crossing timetable.

[0167] S7. Update the logistics timetable, specifically by calculating the number of days between the station arrival date and the base date using structured query language based on the route timetable.

[0168] Please refer to Figure 6. The specific steps for the logistics plan Copy1 are as follows:

[0169] Explanation of the name:

[0170] Traversal refers to visiting each node in a tree exactly once, following a given search path. The operations performed on each node depend on the specific application problem. Traversal is one of the most important operations on binary trees and forms the basis for other operations on binary trees. Of course, the concept of traversal also applies to multi-element collections, such as arrays.

[0171] Map: Used to virtualize an image file as a floppy disk;

[0172] Copy: This is the most commonly used copy command in DOS. It's a command in DOS that allows you to copy several files simultaneously using a single COPY command.

[0173] Number of times the route is traveled.

[0174] S1. Obtain the holiday distinction in the attendance calendar, that is, which day in the attendance calendar is a workday and which day is a restday.

[0175] S2. Obtain the route, pickup cycle and calculate the initial departure date. Obtain the route information for the current logistics plan period, and calculate the initial departure date for this period based on the pickup cycle and final departure date in the route history. If there is no route history, the vehicle will depart on the first working day of this period.

[0176] S3. Obtain route time information;

[0177] S4. Iterate through the route and test whether the bus departs on each day from the start date to the end date. Enter the loop to calculate and identify whether the bus departs from the start date to the end date of the planned period. If the bus departs, store it in the map.

[0178] S5. Before copying, delete database data, specifically the following data tables are deleted based on the base date;

[0179] Planned crossing timetable, planned route timetable, planned logistics instruction timetable;

[0180] S6, Copy the crossing timetable;

[0181] S7, Copy the execution route at any time;

[0182] S8, Copy the execution time of the logistics instruction;

[0183] S9. Back up the route information for this period and the final departure date. First, delete the route history (during the current logistics plan period), and then save the route history (during the current logistics plan period).

[0184] Please refer to Figure 7. The specific steps for copying the crossing time in the logistics plan (Copy2) are as follows:

[0185] Check the departure time and iterate through each day of the cyclical logistics plan.

[0186] If the value is empty, proceed to the next step.

[0187] If the value is not null, then based on the copy date (i.e., the date of arrival at the factory), route name, specific trip number, and whether the daily route trip has departed, check the daily route trip map to see if the trip has departed. If the trip has not departed, then do not copy. For records of RDC gate times, the operation time may differ from the copy date. It is necessary to determine whether the operation date is a working day based on the factory calendar. If it is a rest day, then push it back to a working day. (Strictly speaking, the RDC calendar should be used, but it can be assumed that the RDC calendar is the same as the factory calendar). The copy date data is written to the database.

[0188] Please refer to Figure 8. The specific steps for copying the logistics plan (Copy3) route and time are as follows:

[0189] S1. Query route timetable

[0190] If the value is empty, proceed to the next step.

[0191] If the value is not null, iterate through each day of the cyclical logistics plan. Based on the copy day (i.e., the date of arrival at the factory, route name, and specific trip), check the daily route trip departure map to see if the trip has departed. If the trip has not departed, do not copy. Record the route time for each station on the cyclical route trip, and adjust the arrival and departure dates to the dates relative to the copy day. (Strictly speaking, a station calendar should be used, but for simplicity, a factory calendar is used.) Then, perform validation. The arrival date + time of each station on the route should be later than the departure date + time of the previous station on the route. At the same time, it should also be later than the departure date + time of the last station on the previous copy day on the route. Write the copy day data to the database and return S1.

[0192] Please refer to Figure 9: Logistics Plan Copy4 Logistics Instruction Time Copy The specific steps are as follows:

[0193] S1. Retrieve the logistics schedule.

[0194] If the value is empty, proceed to the next step.

[0195] If the value is not null, iterate through each day of the cyclical logistics plan, and based on the copy day (i.e., the date of arrival at the factory, route name, specific trip), check whether the trip has departed in the daily route trip departure map. If the trip has not departed, do not copy. Adjust the relevant dates in the logistics instructions to the dates corresponding to the copy day. (Strictly speaking, a site calendar should be used, but for the sake of simplicity, a factory calendar is used.) Write the copy day data to the database and return S1.

[0196] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented, in whole or in part, as a computer program product, the computer program product includes one or more computer instructions. When the computer program instructions are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0197] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention shall fall within the scope of the technical solution of the present invention.

Claims

1. A method for supply control of components used in the production of new energy vehicles, characterized in that: At least including: S1. Collect raw data, including supplier basic data, regional distribution center basic data, factory data, process data, and truck data; the supplier basic data includes the location information of each supplier, the distance information between adjacent suppliers, the distance information of each supplier to the regional distribution center, the distance information of each supplier to the factory, and the parts supply information of each supplier. The basic data for the aforementioned regional distribution centers includes the location information of each regional distribution center and the information on temporarily stored parts within that regional distribution center; the factory data includes the location information of each factory, the process information of each factory, the gate information of each factory, and the attendance calendar and time information of each factory; the process data includes the time data and specific process sequence for each process; the truck data includes the vehicle model data and status data for each truck; S2, data processing: periodically procure the required quantity and type of parts from parts suppliers, and based on the factory distribution, the basic data of the regional distribution centers, the types and quantities of parts, the truck data, and the process information, formulate: truck travel routes, loading information and time information, gate pickup time information, and logistics information; S3, based on the data processing results, the factory production management department instructs the logistics supplier's work status under the guidance of the truck travel routes and time information, instructs the gate's work status under the guidance of the gate pickup time information, and instructs the supplier's supply status and the temporary storage status of each regional distribution center under the guidance of the logistics information.

2. The method for supply control of components used in the production of new energy vehicles according to claim 1, characterized in that: The loading information includes the cargo volume and the volume of each component; the cargo volume is greater than the sum of the volumes of each component.

3. The method for supply control of components used in the production of new energy vehicles according to claim 1 or 2, characterized in that: During data processing, if a truck encounters an anomaly en route, an accident occurs in the process, or an anomaly occurs at the production plant, the truck's route, load information and time information, the time information for picking up goods at the crossing, and the logistics information need to be adjusted accordingly based on the anomaly information.

4. The method for supply control of components used in the production of new energy vehicles according to claim 1 or 2, characterized in that: The aforementioned trucks travel on a circular pickup route, specifically: based on the principle of small batches and high frequency, multiple suppliers in a region that need to pick up goods are sequentially linked together to form one or more optimal pickup chains. Then, the trucks depart from the factory, pick up goods from each supplier in turn, and finally return to the factory gate.

5. The method for supply control of components used in the production of new energy vehicles according to claim 1 or 2, characterized in that: The aforementioned truck's route is a circular pickup route, specifically: based on the principle of small batches and high frequency, multiple suppliers that need to pick up goods in a region are sequentially linked to form one or more optimal pickup chains. Then, the truck departs from the regional distribution center to pick up goods from each supplier in turn, returns to the regional distribution center to temporarily store the parts there; finally, the truck departs from the regional distribution center to deliver the parts from the regional distribution center to the designated gate at the factory.

6. A component supply management and control system for new energy vehicle production, characterized in that: At least including: Data acquisition module: Collects raw data, including supplier basic data, regional distribution center basic data, factory data, process data, and truck data; The aforementioned basic supplier data includes each supplier's location information, distance information between adjacent suppliers, distance information from each supplier to the regional distribution center, distance information from each supplier to the factory, and component supply information for each supplier. The basic data for the aforementioned regional distribution centers includes the location information of each regional distribution center and the information on temporarily stored parts within that regional distribution center; the factory data includes the location information of each factory, the process information of each factory, the gate information of each factory, and the attendance calendar and time information of each factory; the process data includes the time data and specific process sequence for each process; the truck data includes the vehicle model data and status data for each truck; the data processing module: periodically purchases the required quantity and type of parts from parts suppliers, and based on the supplier distribution, the basic data of the regional distribution centers, the types and quantities of parts, the truck data, and the process information, it formulates: the truck's travel route, loading information and time information, the gate's cargo pickup time information, and logistics information; The output execution module, based on the data processing results, instructs the logistics supplier's work status according to the truck's travel route and time information, instructs the level crossing's work status according to the level crossing's cargo pickup time information, and instructs each supplier's supply status and each regional distribution center's temporary storage status according to the logistics information.

7. An information data processing terminal for implementing the supply control method for new energy vehicle production components as described in any one of claims 1-5.

8. A computer-readable storage medium comprising instructions that, when executed on a computer, cause the computer to perform the supply control method for components used in the production of new energy vehicles as described in any one of claims 1-5.

9. An apparatus for applying the supply control system for new energy vehicle production components as described in claim 6.

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