Data determination method and device for vehicle parts, processor and electronic equipment
By acquiring and cleaning the initial collected data, and combining the data to automatically calculate the parts usage, the problem of low efficiency in determining the usage of vehicle parts has been solved, and more efficient usage data determination has been achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHANGCHUN FAW INT LOGISTICS CO LTD
- Filing Date
- 2026-03-30
- Publication Date
- 2026-07-21
AI Technical Summary
In existing technologies, the real-time consumption calculation of vehicle parts production lines is highly dependent on manual labor, resulting in tedious, time-consuming, and inefficient calculations.
By acquiring initial data, cleaning and determining target data, and combining it with usage data, the system automatically calculates the usage data of parts, reducing manual intervention.
This improves the efficiency of determining the quantity of vehicle parts, avoids the tedious process of manual calculation, and achieves more efficient determination of quantity data.
Smart Images
Figure CN122434428A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of vehicles, and more specifically, to a method, apparatus, processor, and electronic device for determining data of vehicle parts. Background Technology
[0002] Currently, in the supply chain of vehicle parts, the calculation of real-time consumption of parts on the production line often relies heavily on manual calculations. Moreover, this manual calculation method not only requires exporting data across different systems but also importing the exported data into spreadsheets (Excel) to calculate the real-time consumption of parts on the production line. This results in cumbersome and time-consuming calculations, leading to the technical problem of low efficiency in determining the usage of vehicle parts.
[0003] There is currently no effective solution to the technical problem of low efficiency in determining the usage of the aforementioned vehicle parts. Summary of the Invention
[0004] This application provides a method, apparatus, processor, and electronic device for determining data of vehicle parts, in order to at least solve the technical problem of low efficiency in determining the quantity of vehicle parts.
[0005] According to one aspect of the embodiments of this application, a method for determining data of vehicle parts is provided. The method includes: acquiring initial acquisition data for at least one vehicle, wherein the initial acquisition data is used to represent different types of parts acquired during the production process of the vehicle; determining target acquisition data based on the initial acquisition data, wherein the target acquisition data is used to represent the matching relationship between the acquired different types of parts and different vehicle models, and the usability of the target acquisition data for the production vehicle is higher than the usability of the initial acquisition data for the production vehicle; and determining usage data of the parts based on the target acquisition data and usage data corresponding to the target acquisition data, wherein the usage data is used to represent the quantity of different types of parts used during the production process of the vehicle, and the usage data is used to represent the total quantity of different types of parts used during the production process of different vehicle models.
[0006] Optionally, based on the target acquisition data and the corresponding usage data, the usage data of the parts is determined, including: extracting transaction vehicle data and transaction identification data from the target acquisition data, wherein the transaction vehicle data and transaction identification data correspond one-to-one, the transaction vehicle data is used to indicate the number of vehicles of any vehicle model that have been traded, and the transaction identification data is used to indicate the identification generated when any vehicle model is traded; and based on the transaction vehicle data, transaction identification data, and usage data, the usage data of the parts is determined.
[0007] Optionally, based on the transaction vehicle model data, transaction identification data, and usage data, the usage data of the parts is determined, including: according to the transaction identification data, the transaction vehicle model data and usage data are fused to obtain the usage data.
[0008] Optionally, based on the transaction identifier data, the transaction vehicle model data and usage data are fused to obtain usage data, including: in response to the transaction identifier data being target transaction identifier data, the transaction vehicle model data is determined as target transaction vehicle model data corresponding to the target transaction identifier data, and the usage data is determined as target usage data corresponding to the target transaction identifier data. The target transaction identifier data represents the identifier generated when a vehicle of the target vehicle model is traded; the target transaction vehicle model data represents the number of vehicles of the target vehicle model that have been traded; and the target usage data represents the number of different types of parts used in the production of the target vehicle model. Based on multiple target sub-use data from the target transaction identifier data, target transaction vehicle model data, and target usage data, usage data is determined, where the target sub-use data represents the number of a single type of part used in the production of the target vehicle model.
[0009] Optionally, based on multiple target sub-use data in the target transaction identification data, target transaction vehicle model data, and target usage data, the usage data is determined, including: according to the target transaction identification data, the multiple target sub-use data in the target transaction vehicle model data and target usage data are merged to obtain multiple target usage data, wherein the target usage data is used to represent the total number of a single type of parts used in the process of producing vehicles of the same target vehicle model; and the multiple target usage data are merged to obtain the usage data.
[0010] Optionally, the target data is determined based on the initial data, including: cleaning the initial data; and extracting the target data from the cleaned initial data.
[0011] According to one aspect of the embodiments of this application, a data determination apparatus for vehicle parts is provided. The apparatus may include: an acquisition unit, configured to acquire initial acquisition data for at least one vehicle, wherein the initial acquisition data represents different types of parts acquired during the production of the vehicle; a first determination unit, configured to determine target acquisition data based on the initial acquisition data, wherein the target acquisition data represents the matching relationship between the acquired different types of parts and different vehicle models, and the usability of the target acquisition data for the production vehicle is higher than the usability of the initial acquisition data for the production vehicle; and a second determination unit, configured to determine the usage data of the parts based on the target acquisition data and the usage data corresponding to the target acquisition data, wherein the usage data represents the quantity of different types of parts used during the production of the vehicle, and the usage data represents the total quantity of different types of parts used during the production of different vehicle models.
[0012] According to another aspect of the embodiments of this application, a processor is also provided. The processor is used to run a program, wherein the program is executed by the processor to perform the methods described in the embodiments of this application.
[0013] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.
[0014] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided. This computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the methods of the embodiments of this application.
[0015] According to another aspect of the embodiments of this application, a computer program product is also provided, the computer program product including a computer program, wherein the computer program implements the method in the embodiments of this application when executed by a processor.
[0016] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the method in the embodiments of this application.
[0017] According to another aspect of the embodiments of this application, a computer program is also provided, which, when executed by a processor, implements the methods described in the embodiments of this application.
[0018] In this embodiment, initial data is acquired for at least one vehicle; target data is determined based on the initial data; and the usage data of the parts is determined based on the target data and the corresponding usage data. Since this embodiment, based on the initial data for at least one vehicle, can determine target data for production vehicles with a higher availability than the initial data, and then combine the determined target data with the corresponding usage data, the usage data of the parts can be determined. This achieves the goal of avoiding excessive reliance on manual labor in determining the usage of vehicle parts, thus solving the technical problem of low efficiency in determining the usage of vehicle parts, and ultimately achieving the technical effect of improving the efficiency of determining the usage of vehicle parts. Attached Figure Description
[0019] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:
[0020] Figure 1 This is a schematic diagram illustrating an application scenario of a method for determining data of vehicle parts according to an embodiment of this application;
[0021] Figure 2 This is a flowchart of a method for determining data of vehicle parts according to an embodiment of this application;
[0022] Figure 3 This is a flowchart of a method for calculating vehicle type usage based on actual vehicle sequence, according to an embodiment of this application;
[0023] Figure 4 This is a schematic diagram of a vehicle type usage calculation system based on actual vehicle sequence according to an embodiment of this application;
[0024] Figure 5 This is a schematic diagram of a data determination device for a vehicle part according to an embodiment of this application;
[0025] Figure 6 This is a schematic diagram of an electronic device according to an embodiment of this application. Detailed Implementation
[0026] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present application.
[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0028] According to an embodiment of this application, an embodiment of a method for determining data of vehicle parts is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.
[0029] As an optional implementation, the above-described method for determining vehicle part data can be applied, but is not limited to, to applications such as... Figure 1 The application scenarios shown. Figure 1 This is a schematic diagram illustrating an application scenario of a method for determining data of vehicle parts according to an embodiment of this application, such as... Figure 1 As shown, in the application scenario, terminal device 10 can communicate with server 13 via network 11, but is not limited to this. Server 13 can perform operations on the database, such as write or read data operations. Terminal device 10 may include, but is not limited to, a human-computer interaction screen, a processor, and a memory. The human-computer interaction screen can be used to display virtual machines on mobile terminal 10, but is not limited to this. Vehicle 12 can be used to respond to the aforementioned human-computer interaction operations, execute corresponding operations, or generate corresponding instructions and send the generated instructions to server 13.
[0030] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowcharts, in some cases, the steps shown or described may be executed in a different order than that presented here. Specifically, the data determination method for vehicle parts in this application may include: step S102, acquiring initial acquisition data for at least one vehicle; step S104, determining target acquisition data based on the initial acquisition data; and step S106, determining the usage data of the parts based on the target acquisition data and the usage data corresponding to the target acquisition data.
[0031] It should be noted that all information and data involved in this application (including but not limited to initial collection data, target collection data, usage data, and dosage data) are information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use, and processing of such data must comply with the relevant laws, regulations, and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.
[0032] According to an embodiment of this application, a method for determining data of vehicle parts is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.
[0033] Figure 2 This is a flowchart of a method for determining data of vehicle parts according to an embodiment of this application, such as... Figure 2 As shown, the method may include the following steps.
[0034] Step S201: Obtain initial data for at least one vehicle.
[0035] In the technical solution provided by step S201 of this application, the initial data collected can be used to represent different types of parts collected during the production of vehicles. Optionally, the initial data collected can be real-time data collected through a Manufacturing Operations Management (MOM) system, which can also be referred to as production data.
[0036] In this embodiment, the above-mentioned different types of parts include: body structure and exterior trim assembly parts, interior system assembly parts, electrical and electronic system components, powertrain and chassis functional parts, and optional related components.
[0037] In this embodiment, the aforementioned vehicle body structure and exterior trim assembly parts may include: hinges, sealing strips, trim strips, exterior trim panels, and front and rear bumper assemblies for doors, hoods, and trunks. For example, the aforementioned vehicle body structure and exterior trim assembly parts may be referred to as Part A.
[0038] In this embodiment, the interior system assembly parts may include: instrument panel assembly, center console trim panel, seat fabric and frame, seat belt assembly, headliner material, carpet, sound insulation cotton, and air conditioning vent grille, etc. For example, the aforementioned interior system assembly part may be referred to as part B.
[0039] In this embodiment, the aforementioned electrical and electronic system components may include: wiring harness assemblies (e.g., instrument panel wiring harness, door wiring harness), various sensors (e.g., reversing radar, tire pressure monitoring), control modules (e.g., body control modules), lighting assemblies (e.g., headlights, taillights, daytime running lights), batteries, on-board charging interfaces, and audio system units, etc. For example, the aforementioned electrical and electronic system components may be referred to as component C.
[0040] In this embodiment, the aforementioned powertrain and chassis functional components may include: engine mounts, suspension shock absorbers, steering gear assemblies, brake lines, wheel hubs, tires, exhaust pipes, differentials, and drive shafts, etc. For example, the aforementioned powertrain and chassis functional components may be referred to as component D.
[0041] In this embodiment, the aforementioned optional components may include: an in-vehicle navigation system, a power tailgate, a panoramic sunroof, a power seat memory module, a driver assistance system (e.g., adaptive cruise control sensor, camera), and a smart key assembly. For example, these optional components may be referred to as optional parts.
[0042] In this embodiment, initial data is acquired for at least one vehicle. Optionally, this embodiment uses an MOM system to monitor the production status of at least one production line in the final assembly workshop to obtain initial data. Alternatively, initial data can be obtained by collecting the types and quantities of parts used on at least one production line, thereby achieving the goal of acquiring different types of parts collected during the vehicle production process.
[0043] Step S202: Determine the target data to be collected based on the initial data.
[0044] In the technical solution provided by step S202 of this application, the target acquisition data can be used to represent the matching relationship between different types of acquired parts and different vehicle models. Optionally, the target acquisition data can be the acquisition data to be used in the initial acquisition data, and the acquisition data to be used can include the following fields to be used: acquisition point, acquisition time, chassis number, vehicle identification number (VIN), vehicle model, and sales code, etc.
[0045] In this embodiment, the usability of the target collected data for the production vehicle is higher than that of the initial collected data. For example, the usability of the target collected data for the production vehicle may be, but is not limited to, 98%, while the usability of the initial collected data may be, but is not limited to, 78%. These values are merely illustrative and not specifically limited.
[0046] In this embodiment, after acquiring initial data for at least one vehicle, target data is determined based on the initial data. Optionally, this embodiment performs data cleaning on the acquired initial data to obtain the target data, thereby achieving the goal of determining the matching relationship between different types of collected parts and different vehicle models.
[0047] Optionally, invalid data is identified from the initial data collection. Invalid data may include VIN codes, engine numbers, sales order numbers, and blank data, with blank data being considered invalid. Invalid data is then deleted from the initial data collection. Next, from the remaining initial data collection, the data whose availability to the production vehicle is higher than that of the initial data collection is identified as target data.
[0048] Step S203: Based on the target acquisition data and the corresponding usage data, determine the usage data of the parts. The usage data is used to represent the number of different types of parts used in the process of producing vehicles, and the usage data is used to represent the total number of different types of parts used in the process of producing different vehicle models.
[0049] In the technical solution provided in step S203 of this application, the usage data can be used to represent the quantity of different types of parts used in the process of vehicle production. Optionally, the usage data can be part information synchronized through a Bill of Materials (BOM) system.
[0050] In this embodiment, the aforementioned usage data can be used to represent the total number of different types of parts used in the production process of different vehicle models. Optionally, the aforementioned usage data may also be referred to as vehicle model usage information in the following text.
[0051] In this embodiment, after determining the target acquisition data based on the initial acquisition data, the usage data of the parts is determined based on the target acquisition data and the corresponding usage data. Optionally, based on the determined target acquisition data, this embodiment can determine transaction data from the target acquisition data. The transaction data can be used to represent the number of vehicles of any particular model that have been traded, and the identifier generated when a vehicle of any particular model is traded. Then, by combining the transaction data and the usage data corresponding to the target acquisition data, the usage data of the parts can be determined, thereby achieving the goal of determining the total number of different types of parts used in the production of different vehicle models.
[0052] In steps S201 to S203 of this application, initial data collection for at least one vehicle is obtained; target data collection is determined based on the initial data collection; and the usage data of the parts is determined based on the target data collection and the corresponding usage data. Since this embodiment of the application, based on the initial data collection for at least one vehicle, can determine target data collection for production vehicles with a higher availability than the initial data collection, and then combine the determined target data collection with the corresponding usage data, the usage data of the parts can be determined. This achieves the goal of avoiding excessive reliance on manual labor in determining the usage of vehicle parts, thereby solving the technical problem of low efficiency in determining the usage of vehicle parts, and ultimately achieving the technical effect of improving the efficiency of determining the usage of vehicle parts.
[0053] The method described in this embodiment will be further described below.
[0054] As an optional embodiment, step S203, based on the target acquisition data and the corresponding usage data, determines the usage data of the parts, including: extracting transaction vehicle data and transaction identifier data from the target acquisition data, wherein the transaction vehicle data and the transaction identifier data correspond one-to-one, the transaction vehicle data is used to indicate the number of vehicles of any vehicle model that have been traded, and the transaction identifier data is used to indicate the identifier generated when any vehicle model is traded; and determining the usage data of the parts based on the transaction vehicle data, the transaction identifier data, and the usage data.
[0055] In this embodiment, the aforementioned vehicle model data and transaction identifier data correspond one-to-one.
[0056] In this embodiment, the aforementioned vehicle model data is used to represent the number of vehicles of any given model that have been traded. For example, if any given model corresponds to sales code 1, then the aforementioned vehicle model data can be used to represent the number of vehicles of the model corresponding to sales code 1 that have been traded. This is merely an example and is not intended to be specific.
[0057] In this embodiment, the transaction identifier data is used to represent an identifier generated when any vehicle model is traded. For example, the transaction identifier data can be used to represent sales code 1 generated when any vehicle model is traded, or the transaction identifier data can be used to represent sales code 2 generated when any vehicle model is traded, or the transaction identifier data can be used to represent sales code 3 generated when any vehicle model is traded. The numerical values are only used as examples and are not specifically limited.
[0058] In this embodiment, after determining the target data based on the initial collected data, the vehicle model data and transaction identifier data are extracted from the target collected data. Optionally, in this embodiment, based on the determined target collected data, transaction data can be extracted from the target collected data. Then, the transaction data is segmented to obtain the vehicle model data and transaction identifier data.
[0059] In this embodiment, after extracting the transaction vehicle model data and transaction identification data from the target data, the usage data of the parts is determined based on the transaction vehicle model data, transaction identification data, and usage data.
[0060] Optionally, this embodiment, based on the extracted vehicle model data and transaction identification data, combines these data with usage data to determine the quantity of parts used. For example, by fusing the vehicle model data and the parts information synchronized from the BOM system according to the sales code, vehicle model usage information can be obtained. This achieves the goal of determining the total quantity of different types of parts used in the production of different vehicle models, thereby improving the accuracy of usage data.
[0061] For example, by combining the number of vehicles that have been traded for the model corresponding to sales code 1 with the parts information of the vehicle corresponding to sales code 1, we can obtain the total number of different types of parts used in the production of the vehicle corresponding to sales code 1. This is just an example and is not a specific limitation.
[0062] The following section further describes the steps of determining the usage data of parts based on the transaction vehicle model data, transaction identification data, and usage data in this embodiment.
[0063] As an optional implementation method, the usage data of parts is determined based on the transaction vehicle model data, transaction identification data, and usage data, including: fusing the transaction vehicle model data and usage data according to the transaction identification data to obtain the usage data.
[0064] In this embodiment, after extracting the transaction vehicle data and transaction identification data from the target data, the transaction vehicle data and usage data are fused according to the transaction identification data to obtain usage data.
[0065] Optionally, this embodiment integrates the number of completed transactions for the vehicle model corresponding to sales code 2 and the parts information of the vehicle model corresponding to sales code 2 to obtain the total number of different types of parts used in the production of the vehicle model corresponding to sales code 2. This achieves the goal of determining the total number of different types of parts used in the production of different vehicle models, thereby improving the accuracy of usage data.
[0066] Optionally, this embodiment integrates the number of completed transactions for the vehicle model corresponding to sales code 3 and the parts information of the vehicle model corresponding to sales code 3 to obtain the total number of different types of parts used in the production of the vehicle model corresponding to sales code 3.
[0067] The following section further describes the steps of fusing transaction vehicle data and usage data according to transaction identifier data to obtain usage data in this embodiment.
[0068] As an optional implementation, data fusion is performed on the transaction vehicle model data and usage data according to the transaction identifier data to obtain usage data, including: in response to the transaction identifier data being target transaction identifier data, determining the transaction vehicle model data as target transaction vehicle model data corresponding to the target transaction identifier data, and determining the usage data as target usage data corresponding to the target transaction identifier data, wherein the target transaction identifier data is used to represent the identifier generated when a vehicle of the target vehicle model is traded, the target transaction vehicle model data is used to represent the number of vehicles of the target vehicle model that have been traded, and the target usage data is used to represent the number of different types of parts used in the production process of the target vehicle model; and based on multiple target sub-use data in the target transaction identifier data, target transaction vehicle model data, and target usage data, determining usage data, wherein the target sub-use data is used to represent the number of a single type of part used in the production process of the target vehicle model.
[0069] In this embodiment, the aforementioned target transaction identifier data can be used to represent an identifier generated when a vehicle of the target model is traded. The generated identifier can be represented by a sales code, and there can be multiple sales codes. For example, the aforementioned sales code may also be referred to as a sales code in the following text; this is merely an example and not a specific limitation.
[0070] In this embodiment, the target vehicle model data can be used to represent the number of vehicles of the target model that have been traded. For example, if the target vehicle model is the model corresponding to sales code 2, then the target vehicle model data can be used to represent the number of vehicles of the model corresponding to sales code 2 that have been traded. This is only an example and is not a specific limitation.
[0071] In this embodiment, the target usage data can be used to represent the number of different types of parts used in the production process of the target vehicle model. For example, if the target vehicle model is the model corresponding to sales code 2, then the target usage data can be used to represent the number of different types of parts used in the production process of the vehicle model corresponding to sales code 2.
[0072] In this embodiment, after extracting the transaction vehicle data and transaction identifier data from the target collected data, in response to the transaction identifier data being the target transaction identifier data, the transaction vehicle data is determined as the target transaction vehicle data corresponding to the target transaction identifier data, and the usage data is determined as the target usage data corresponding to the target transaction identifier data.
[0073] Optionally, this embodiment, based on the extracted vehicle model data and transaction identifier data, compares the transaction identifier data with the target transaction identifier data to obtain a comparison result. This comparison result can be used to represent the data relationship between the transaction identifier data and the target transaction identifier data. If the comparison result indicates that the transaction identifier data is the target transaction identifier data, then the vehicle model data is determined as the target vehicle model data corresponding to the target transaction identifier data, and the usage data is determined as the target usage data corresponding to the target transaction identifier data.
[0074] In this embodiment, the target sub-use data can be used to represent the quantity of a single type of part used in the production process of a vehicle of the target model. For example, if the target model is the model corresponding to sales code 3, then the target sub-use data can be used to represent the quantity of a single type of part used in the production process of the vehicle of the model corresponding to sales code 3.
[0075] In this embodiment, after determining the transaction vehicle model data as the target transaction vehicle model data corresponding to the target transaction vehicle model data in response to the transaction identification data being the target transaction identification data, and determining the usage data as the target usage data corresponding to the target transaction identification data, the usage data is determined based on multiple target sub-usage data among the target transaction identification data, target transaction vehicle model data, and target usage data.
[0076] Optionally, this embodiment, based on the determined vehicle model data and usage data, fuses the target vehicle model data and the various target sub-usage data according to the target transaction identifier data to obtain multiple target usage data. Based on these multiple target usage data, the usage data of parts can be determined, thereby achieving the goal of determining the total quantity of different types of parts used in the production of different vehicle models, thus realizing the technical effect of improving the accuracy of usage data.
[0077] For example, by combining the number of completed transactions for the vehicle model corresponding to sales code 3 with the sub-part information of the same vehicle model corresponding to sales code 3, we can obtain the total number of different types of parts used in the production of the same vehicle model corresponding to sales code 3. The aforementioned sub-part information can be used to represent the number of a single type of part used in the production of the vehicle model corresponding to sales code 3.
[0078] The following section further describes the steps of determining usage data based on multiple target sub-usage data from the target transaction identifier data, target transaction vehicle model data, and target usage data in this embodiment.
[0079] As an optional implementation method, the usage data is determined based on multiple target sub-use data in the target transaction identification data, target transaction vehicle model data, and target usage data. This includes: according to the target transaction identification data, fusing multiple target sub-use data in the target transaction vehicle model data and target usage data to obtain multiple target usage data, wherein the target usage data is used to represent the total number of a single type of parts used in the process of producing vehicles of the same target vehicle model; and fusing multiple target usage data to obtain the usage data.
[0080] In this embodiment, the target usage data can be used to represent the total number of a single type of part used in the production of vehicles of the same target model. Optionally, the target usage data may include: first target usage data, second target usage data, third target usage data, and fourth target usage data, wherein the first target usage data can be used to represent the total number of part A used in the production of vehicles of the same model corresponding to the sales code, the second target usage data can be used to represent the total number of part B used in the production of vehicles of the same model corresponding to the sales code, the third target usage data can be used to represent the total number of part C used in the production of vehicles of the same model corresponding to the sales code, and the fourth target usage data can be used to represent the total number of part D used in the production of vehicles of the same model corresponding to the sales code.
[0081] In this embodiment, in response to the transaction identifier data being target transaction identifier data, the transaction vehicle model data is determined as the target transaction vehicle model data corresponding to the target transaction identifier data, and the usage data is determined as the target usage data corresponding to the target transaction identifier data. Then, according to the target transaction identifier data, multiple target sub-usage data in the target transaction vehicle model data and the target usage data are fused to obtain multiple target usage data.
[0082] Optionally, by multiplying the number of vehicles that have been traded for the model corresponding to sales code 2 with the sub-part information of vehicles of the same model corresponding to sales code 2, the total number of a single type of part used in the production of vehicles of the same model corresponding to sales code 2 can be obtained. The aforementioned sub-part information can be used to represent the number of a single type of part used in the production of vehicles of the model corresponding to sales code 2.
[0083] For example, multiplying the number of completed transactions for vehicles corresponding to sales code 2 with the number of type A parts used in the production of vehicles of the same model corresponding to sales code 2 yields the total number of type A parts used in the production of vehicles of the same model corresponding to sales code 2. Similarly, multiplying the number of completed transactions for vehicles corresponding to sales code 2 with the number of type B parts used in the production of vehicles of the same model corresponding to sales code 2 yields the total number of type B parts used in the production of vehicles of the same model corresponding to sales code 2. The same applies to the production of vehicles of the same model corresponding to sales code 2 with the number of type C parts used in the production of vehicles of the same model corresponding to sales code 2. Finally, multiplying the number of completed transactions for vehicles corresponding to sales code 2 with the number of type D parts used in the production of vehicles of the same model corresponding to sales code 2 yields the total number of type D parts used in the production of vehicles of the same model corresponding to sales code 2.
[0084] In this embodiment, after fusing multiple target sub-use data from the target vehicle model data and target usage data according to the target transaction identifier data to obtain multiple target usage data, the multiple target usage data are then fused together to obtain usage data.
[0085] Optionally, data fusion of multiple first-target usage data can yield first-fused usage data, which can represent the total quantity of the same part A used in the production of different vehicle models. Data fusion of multiple second-target usage data can yield second-fused usage data, which can represent the total quantity of the same part B used in the production of different vehicle models. Data fusion of multiple third-target usage data can yield third-fused usage data, which can represent the total quantity of the same part C used in the production of different vehicle models. Data fusion of multiple fourth-target usage data can yield fourth-fused usage data, which can represent the total quantity of the same part D used in the production of different vehicle models. By using the aforementioned first, second, third, and fourth fusion usage data as part usage data, the total number of different types of parts used in the production of different vehicle models can be determined, thereby achieving the technical effect of improving the accuracy of usage data.
[0086] The steps for determining the target data based on the initial data collected in this embodiment will be further described below.
[0087] As an optional embodiment, step S202, determining the target data based on the initial data, includes: cleaning the initial data; and extracting the target data from the cleaned initial data.
[0088] In this embodiment, after acquiring initial data for at least one vehicle, the initial data is cleaned. Optionally, based on the acquired initial data, this embodiment identifies invalid data from the initial data and then deletes the invalid data.
[0089] For example, invalid fields, including VIN codes, engine numbers, and sales order numbers, as well as blank data, are removed from the real-sequence data, thereby achieving the purpose of cleaning the initially collected data.
[0090] In this embodiment, after cleaning the initial collected data, target collected data is extracted from the cleaned initial collected data. Optionally, based on the cleaned initial collected data, this embodiment extracts usable collected data from the cleaned initial collected data that has a higher degree of usability to the production vehicle than the initial collected data, and identifies the aforementioned usable collected data as target collected data. This achieves the goal of extracting target collected data, thereby improving the accuracy of the target collected data.
[0091] For example, from the cleaned real-sequence data, the following fields that need to be used are selected: collection point, collection time, chassis number, VIN code, vehicle model and sales code, etc.
[0092] In this embodiment, initial data is acquired for at least one vehicle; target data is determined based on the initial data; and the usage data of the parts is determined based on the target data and the corresponding usage data. Since this embodiment, based on the initial data for at least one vehicle, can determine target data for production vehicles with a higher availability than the initial data, and then combine the determined target data with the corresponding usage data, the usage data of the parts can be determined. This achieves the goal of avoiding excessive reliance on manual labor in determining the usage of vehicle parts, thus solving the technical problem of low efficiency in determining the usage of vehicle parts, and ultimately achieving the technical effect of improving the efficiency of determining the usage of vehicle parts.
[0093] The technical solutions of the embodiments of this application will be illustrated below with reference to preferred embodiments.
[0094] Currently, in the supply chain of vehicle parts, the calculation of real-time consumption of parts on the production line often relies heavily on manual calculations. Moreover, this manual calculation method not only requires exporting data across different systems but also importing the exported data into Excel to calculate the real-time consumption of parts on the production line. This results in tedious and time-consuming calculations, leading to the technical problem of low efficiency in determining the usage of vehicle parts.
[0095] To address the aforementioned technical problems, this application proposes a method for determining information about vehicle parts. Based on initial data collected for at least one vehicle, target data can be determined for production vehicles with a higher availability than the initial data. Then, by combining the determined target data with the corresponding usage data, the usage data of the parts can be determined. This achieves the goal of avoiding excessive reliance on manual labor in determining the usage of vehicle parts, thereby solving the technical problem of low efficiency in determining the usage of vehicle parts and ultimately improving the technical effect of determining the efficiency of vehicle parts usage.
[0096] In this embodiment, by executing a vehicle model usage calculation method based on actual vehicle sequence, the total number of different types of parts used in the production of different vehicle models can be calculated. For example, Figure 3 This is a flowchart illustrating a method for calculating vehicle type usage based on actual vehicle sequence, according to an embodiment of this application. Figure 3 As shown, the method may include the following steps.
[0097] Step 301: Develop an interface for the Manufacturing Operations Management (MOM) system and push production data.
[0098] In the technical solution provided in step S301 of this application, the MOM system can statistically analyze the specific production information of each line in the final assembly workshop in real time. This real-time statistical analysis refers to real-time data collection point statistics. The workshop production line real-time data collected by the MOM system is pushed to the instruction system database in a lightweight, easy-to-read, cross-platform data exchange format (JavaScript Object Notation, or JSON for short). For example, the collected real-time data can be presented in tabular form.
[0099] For example, the MOM system can collect real-time data. For instance, if 30 vehicles pass the final assembly line check, of which 20 correspond to model number 1, 5 to model number 2, and 5 to model number 3, the MOM system can automatically collect real-time data for these 30 vehicles in the background.
[0100] After pushing production data, step 302 is executed to receive real-time data from the MOM system and clean and organize the real-time data.
[0101] In the technical solution provided in step S302 of this application, the fields to be used are selected. These fields may include: collection point, collection time, chassis number, VIN code, vehicle model, and sales code. Then, invalid fields are cleaned. These invalid fields may include: vehicle code, engine number, sales order number, and invalid data, which may be blank data. When multiple collection times are simultaneously identified for a given collection point, chassis number, and VIN code, only the first time is recorded, and subsequent times are cleared.
[0102] After receiving the real-time data from the MOM system and cleaning and organizing the real-time data, step 303 is executed to synchronize the part information in the backend of the bill of materials system.
[0103] In the technical solution provided by step S303 of this application, the part information can be used to indicate the quantity of parts corresponding to the sales code.
[0104] In this embodiment, the parts information in the BOM system backend is synchronized. Each vehicle model corresponds to a sales code, and each sales code corresponds to the usage information of 2000-3000 parts. For example, the above usage information can be presented in tabular form.
[0105] For example, a BOM system can synchronize part information. The part information above could be as follows: Sales code 1 corresponds to a usage of 2 units of part A, 1 unit of part B, and 2 units of part C; Sales code 2 corresponds to a usage of 0 units of part A, 2 units of part B, 0 units of part C, and 1 unit of part D; Sales code 3 corresponds to a usage of 0 units of part A, 2 units of part B, and 0 units of part C. This is merely an example and not a specific limitation.
[0106] After synchronizing the part information in the BOM system backend, proceed to step 304, select the line collection point and the time period passing the point, and calculate the vehicle usage information passing this collection point and this time period.
[0107] In the technical solution provided in step S304 of this application, the assembly line start time is selected as 11:30-12:30 or 13:30-14:30. For example, the collection table corresponding to the line can be shown in Table 1 below. This is only an example and is not specifically limited.
[0108] For example, a vehicle model usage calculation system based on actual vehicle sequence can calculate the usage information of parts for 30 vehicles. For instance, the usage of part A is 20. 2+5 0+5 0=40, the quantity of part B is: 20 1+5 2+5 2=40, the quantity of part C is: 20 2+5 0+5 0=40, the quantity of part D is 20. 0+5 1+5 0 = 5.
[0109] Table 1. Line Correspondence Acquisition Table
[0110]
[0111] After calculating the vehicle usage information for this collection point and this time period, step 305 is executed to output the vehicle usage information for daily maintenance and use of the vehicles at the production site.
[0112] In the technical solution provided in step S305 of this application, the on-site use is divided into warehouse keeper teams (information calculation) and on-site teams (parts delivery) according to the different job roles.
[0113] In this embodiment, the usage calculation system can automatically capture MOM (Model Number) real-time data. The Kanban room can disassemble and maintain the BOM (Bill of Materials) system, which can automatically calculate vehicle model information and the corresponding parts usage. On-site teams can query vehicle model information and usage.
[0114] For example, a vehicle type usage calculation method based on actual vehicle sequence can be executed through a vehicle type usage calculation system based on actual vehicle sequence. For example, Figure 4 This is a schematic diagram of a vehicle type usage calculation system based on actual vehicle sequence according to an embodiment of this application, such as... Figure 4 As shown, the vehicle model usage calculation system 400 based on actual vehicle sequence can be connected to the MOM system 401 and the BOM system 402 respectively, and the BOM system 402 can be connected to the MOM system 401.
[0115] In this embodiment, the MOM system 401 collects real-time data related to vehicle models and transmits this data to the vehicle model usage calculation system 400 and the BOM system 402 based on the actual vehicle sequence. The BOM system 402 synchronizes part information and transmits this information to the vehicle model usage calculation system 400 based on the actual vehicle sequence. The vehicle model usage calculation system 400 calculates the total quantity of different types of parts used in the production of different vehicle models.
[0116] In this embodiment, initial data is acquired for at least one vehicle; target data is determined based on the initial data; and the usage data of the parts is determined based on the target data and the corresponding usage data. Since this embodiment, based on the initial data for at least one vehicle, can determine target data for production vehicles with a higher availability than the initial data, and then combine the determined target data with the corresponding usage data, the usage data of the parts can be determined. This achieves the goal of avoiding excessive reliance on manual labor in determining the usage of vehicle parts, thus solving the technical problem of low efficiency in determining the usage of vehicle parts, and ultimately achieving the technical effect of improving the efficiency of determining the usage of vehicle parts.
[0117] According to an embodiment of this application, a data determination device for vehicle parts is also provided. It should be noted that this data determination device for vehicle parts can be used to execute a data determination method for vehicle parts according to one of the embodiments.
[0118] Figure 5 This is a schematic diagram of a data determination device for a vehicle part according to an embodiment of this application. Figure 5 As shown, the data determination device 500 for the vehicle parts may include: an acquisition unit 501, a first determination unit 502, and a second determination unit 503.
[0119] Acquisition unit 501 is used to acquire initial acquisition data for at least one vehicle, wherein the initial acquisition data is used to represent different types of parts acquired during the vehicle production process.
[0120] The first determining unit 502 is used to determine target acquisition data based on the initial acquisition data. The target acquisition data is used to represent the matching relationship between different types of parts and different vehicle models. The usability of the target acquisition data for production vehicles is higher than that of the initial acquisition data for production vehicles.
[0121] The second determining unit 503 is used to determine the usage data of parts based on the target acquisition data and the usage data corresponding to the target acquisition data. The usage data is used to represent the number of different types of parts used in the process of producing vehicles, and the usage data is used to represent the total number of different types of parts used in the process of producing different models of vehicles.
[0122] Optionally, the second determining unit 503 may include: a first extraction module, used to extract transaction vehicle data and transaction identifier data from the target collected data, wherein the transaction vehicle data and the transaction identifier data correspond one-to-one, the transaction vehicle data is used to indicate the number of vehicles of any vehicle type that have been traded, and the transaction identifier data is used to indicate the identifier generated when any vehicle type is traded; and a determining module, used to determine the usage data of parts based on the transaction vehicle data, the transaction identifier data, and the usage data.
[0123] Optionally, the determining module may include: a determining submodule, used to perform data fusion on the transaction vehicle model data and usage data according to the transaction identifier data to obtain usage data.
[0124] Optionally, the determination submodule can perform the following steps to fuse transaction vehicle data and usage data according to transaction identifier data to obtain usage data: In response to the transaction identifier data being target transaction identifier data, the transaction vehicle data is determined as target transaction vehicle data corresponding to the target transaction identifier data, and the usage data is determined as target usage data corresponding to the target transaction identifier data. Here, the target transaction identifier data represents the identifier generated when a vehicle of the target vehicle model is traded; the target transaction vehicle data represents the number of vehicles of the target vehicle model that have been traded; and the target usage data represents the number of different types of parts used in the production of the target vehicle model. Based on multiple target sub-use data from the target transaction identifier data, target transaction vehicle data, and target usage data, usage data is determined, where the target sub-use data represents the number of a single type of part used in the production of the target vehicle model.
[0125] Optionally, the determination submodule can determine the usage data based on multiple target sub-use data in the target transaction identification data, target transaction vehicle model data, and target usage data by performing the following steps: according to the target transaction identification data, the multiple target sub-use data in the target transaction vehicle model data and target usage data are merged to obtain multiple target usage data, wherein the target usage data is used to represent the total number of a single type of parts used in the process of producing vehicles of the same target vehicle model; the multiple target usage data are merged to obtain the usage data.
[0126] Optionally, the first determining unit 502 may include: a cleaning module for cleaning the initial collected data; and a second extraction module for extracting the target collected data from the cleaned initial collected data.
[0127] In this embodiment, a data determination device for vehicle parts is provided. The device may include: an acquisition unit for acquiring initial collected data for at least one vehicle, wherein the initial collected data represents different types of parts collected during vehicle production; a first determination unit for determining target collected data based on the initial collected data, wherein the target collected data represents the matching relationship between the collected different types of parts and different vehicle models, and the usability of the target collected data for the production vehicle is higher than that of the initial collected data; and a second determination unit for determining the usage data of the parts based on the target collected data and the corresponding usage data, wherein the usage data represents the quantity of different types of parts used during vehicle production, and the usage data represents the total quantity of different types of parts used during the production of different vehicle models. This achieves the goal of avoiding excessive reliance on manual labor in determining the usage of vehicle parts, thereby solving the technical problem of low efficiency in determining the usage of vehicle parts and achieving the technical effect of improving the efficiency of determining the usage of vehicle parts.
[0128] According to an embodiment of this application, a processor is also provided for running a program, wherein the program is executed by the processor to perform the methods described in the embodiment.
[0129] According to an embodiment of this application, an electronic device is also provided. Figure 6 This is a schematic diagram of an electronic device according to an embodiment of this application, such as... Figure 6 As shown, the electronic device 600 may include a memory 610 and a processor 620, wherein the memory 610 is used to store an executable program; and the processor 620 is used to run the program stored in the memory 610, wherein the program executes the methods in various embodiments of this application when it runs.
[0130] In this application, "multiple" refers to two or more.
[0131] In this application, unless otherwise expressly defined, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.
[0132] The terms “first,” “second,” “third,” “fourth,” etc., in this application (if present) are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.
[0133] In this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, in this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.
[0134] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided. This computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method described in the embodiments.
[0135] Computer-readable storage media, also known as computer storage media, may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. These propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable storage media can transmit, propagate, or transfer programs for use by or in conjunction with an instruction execution system, apparatus, or device.
[0136] The program code contained in a computer-readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, radio frequency, or any suitable combination thereof.
[0137] According to an embodiment of this application, a computer program product is also provided, which includes a computer program, wherein the computer program, when executed by a processor, implements the method in the embodiment.
[0138] According to an embodiment of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the method described in the embodiment.
[0139] According to an embodiment of this application, a computer program is also provided, which, when executed by a processor, implements the method described in the embodiment.
[0140] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.
[0141] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.
[0142] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.
[0143] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0144] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.
[0145] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to related technologies, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.
[0146] The above are merely preferred embodiments of this application. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.
Claims
1. A method for determining data of vehicle parts, characterized in that, include: Acquire initial acquisition data for at least one of the vehicles, wherein the initial acquisition data is used to represent different types of parts acquired during the production of the vehicle; Based on the initial data collected, target data is determined, wherein the target data is used to represent the matching relationship between the different types of parts collected and different vehicle models, and the usability of the target data for producing the vehicle is higher than that of the initial data for producing the vehicle. Based on the target acquisition data and the corresponding usage data, the usage data of the parts is determined, wherein the usage data is used to represent the number of the different types of parts used in the process of producing the vehicle, and the usage data is used to represent the total number of the different types of parts used in the process of producing the different vehicle models.
2. The method according to claim 1, characterized in that, Based on the target acquisition data and the corresponding usage data, the usage data of the part is determined, including: From the target data, transaction vehicle data and transaction identifier data are extracted. The transaction vehicle data and the transaction identifier data correspond one-to-one. The transaction vehicle data is used to indicate the number of vehicles of any vehicle type that have been traded. The transaction identifier data is used to indicate the identifier generated when any vehicle of any vehicle type is traded. Based on the vehicle model data, the transaction identification data, and the usage data, the usage data of the parts is determined.
3. The method according to claim 2, characterized in that, Based on the transaction vehicle model data, the transaction identification data, and the usage data, the usage data of the parts is determined, including: Based on the transaction identifier data, the transaction vehicle data and the usage data are fused to obtain the usage data.
4. The method according to claim 3, characterized in that, Based on the transaction identifier data, the transaction vehicle data and the usage data are fused to obtain the usage data, including: In response to the transaction identifier data being target transaction identifier data, the transaction vehicle model data is determined as target transaction vehicle model data corresponding to the target transaction identifier data, and the usage data is determined as target usage data corresponding to the target transaction identifier data. The target transaction identifier data represents an identifier generated when a vehicle of the target vehicle model is traded; the target transaction vehicle model data represents the number of vehicles of the target vehicle model that have been traded; and the target usage data represents the number of different types of parts used during the production of the target vehicle model. Based on the target transaction identifier data, the target transaction vehicle model data, and various target sub-use data in the target usage data, the usage data is determined, wherein the target sub-use data is used to represent the number of a single type of part used in the process of producing the vehicle of the target vehicle model.
5. The method according to claim 4, characterized in that, Based on the target transaction identifier data, the target transaction vehicle model data, and various target sub-usage data in the target usage data, the usage data is determined, including: According to the target transaction identifier data, the target transaction vehicle model data and the target usage data are respectively fused to obtain multiple target usage data, wherein the target usage data is used to represent the total number of parts of the single type used in the process of producing vehicles of the same target vehicle model; The usage data is obtained by fusing multiple target usage data.
6. The method according to any one of claims 1 to 5, characterized in that, Based on the initial data collected, the target data to be collected is determined, including: The initial collected data is cleaned; The target data is extracted from the cleaned initial data.
7. An information data device for vehicle parts, characterized in that, include: An acquisition unit is configured to acquire initial acquisition data for at least one of the vehicles, wherein the initial acquisition data is used to represent different types of parts acquired during the production of the vehicle; The first determining unit is used to determine target acquisition data based on the initial acquisition data, wherein the target acquisition data is used to represent the matching relationship between the acquired different types of parts and different vehicle models, and the usability of the target acquisition data for producing the vehicle is higher than the usability of the initial acquisition data for producing the vehicle. The second determining unit is used to determine the usage data of the parts based on the target acquisition data and the usage data corresponding to the target acquisition data, wherein the usage data is used to indicate the number of the different types of parts used in the process of producing the vehicle, and the usage data is used to indicate the total number of the different types of parts used in the process of producing the different models of vehicles.
8. A processor, characterized in that, The processor is used to run a program, wherein the program is executed by the processor to perform the method according to any one of claims 1 to 6.
9. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 1 to 6.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the computer-readable storage medium is located to perform the method according to any one of claims 1 to 6.