Part storage location determination method and device, vehicle and storage medium

Abstract

The invention discloses a part storage location determining method and device, a vehicle and a storage medium, and the part storage location determining method comprises the steps: obtaining a plurality of part parameters of a plurality of parts and a warehouse size value of a target warehouse; according to the multiple part parameters, multiple target projection area values are determined, and the target projection area values are used for representing the occupied area values of the parts; classifying the plurality of parts according to the plurality of target projection area values and the plurality of part parameters to obtain a classification result; and according to the warehouse size value and the classification result, multiple target storage locations of the multiple parts are determined, and the multiple parts are in one-to-one correspondence with the multiple target storage locations. The technical problem that in the prior art, the storage location utilization rate of a part storage warehouse is low is solved.

Description

Technical Field

[0001] The present invention relates to the field of automated control technology, and in particular to a method, device, vehicle and storage medium for determining a parts warehouse location. Background Art

[0002] Large parts refer to parts that are large in size or mass and have low consumption in a single production cycle, such as tires, motors, pumps, etc. Their warehouse management costs account for a high proportion of the total costs, and traditional management methods have risks, such as part failure leading to production stoppages, assembly errors, and part loss, which cannot meet the requirements of lean manufacturing.

[0003] Therefore, large parts are typically managed using yards or shelf storage. Yard storage utilizes floor space and is less expensive and more efficient than shelf storage. However, this presents the following challenges: Large amounts of unused inventory accumulate on the floor, wasting space resources; regular manual inventory checks are time-consuming and labor-intensive, making it difficult to identify safety hazards; parts are susceptible to moisture, rust, and wear; and damaged parts cannot be traced, impacting product quality. Shelf storage, on the other hand, suffers from low space utilization, insufficient storage capacity, and low storage efficiency.

[0004] Large parts storage often relies on material handling equipment such as forklifts, stackers, and electric hoists. These parts have low turnover rates, are bulky, and require long transport distances, placing high demands on the performance of this equipment and increasing maintenance costs. Traditional storage yards or rack layouts fail to consider equipment movement paths and efficiency, resulting in long transport paths, low efficiency, and heavy equipment loads.

[0005] To address the above issues, no effective solutions have been proposed so far. Summary of the Invention

[0006] The embodiments of the present invention provide a method, device, vehicle and storage medium for determining a parts warehouse location, so as to at least solve the technical problem of low utilization rate of parts storage warehouse locations in the prior art.

[0007] According to one embodiment of the present invention, a method for determining a parts storage location is provided, comprising: obtaining multiple part parameters of multiple parts and a warehouse size value of a target warehouse; determining multiple target projected area values based on the multiple part parameters, wherein the target projected area values are used to characterize the floor space values of the parts; classifying the multiple parts based on the multiple target projected area values and the multiple part parameters to obtain classification results; and determining multiple target storage locations for the multiple parts based on the warehouse size value and the classification results, wherein the multiple parts correspond one-to-one to the multiple target storage locations.

[0008] Optionally, the method for determining the parts storage location also includes: determining multiple initial projected area values based on multiple parts storage values and multiple part size values; determining multiple target stacking layers of multiple parts based on multiple part attributes; and adjusting the initial projected area value of each part based on the target stacking layer number to obtain the target projected area value.

[0009] Optionally, the method for determining the parts warehouse location also includes: obtaining multiple daily consumption values, multiple parts delivery distances and multiple quality compliance probability values corresponding to multiple parts; determining multiple initial parts reserve values for the multiple parts based on the quality compliance probability values, wherein the multiple parts correspond one-to-one to the multiple initial parts reserve values; adjusting the multiple initial parts reserve values based on the multiple daily consumption values and the multiple parts delivery distances to obtain multiple parts reserve values.

[0010] Optionally, the method for determining the parts warehouse location also includes: for each part among the multiple parts, determining the initial part category corresponding to each part based on the target projection area value; adjusting the initial part category of each part based on the part size value to obtain the target part category corresponding to each part to obtain a classification result.

[0011] Optionally, the method for determining the parts storage location also includes: determining multiple storage location areas based on warehouse size values; establishing target correspondences between multiple storage location areas and multiple target part categories; and determining the target storage location area for each part based on the target correspondences and the target part categories.

[0012] Optionally, the method for determining the parts storage location also includes: for each part, in response to determining the target storage location area, detecting the area occupancy of the target storage location area to obtain a detection result; in response to the detection result indicating that the area occupancy is a preset target occupancy, re-determining the target storage location area according to the part size value.

[0013] According to one embodiment of the present invention, a device for determining a parts warehouse location is also provided, including: an acquisition module for acquiring multiple part parameters of multiple parts and a warehouse size value of a target warehouse; a first determination module for determining multiple target projection area values based on the multiple part parameters, wherein the target projection area value is used to characterize the floor area value of the part; a classification module for classifying multiple parts according to the multiple target projection area values and the multiple part parameters to obtain classification results; a second determination module for determining multiple target warehouse locations of multiple parts according to the warehouse size value and the classification results, wherein the multiple parts correspond one-to-one to the multiple target warehouse locations.

[0014] Optionally, the first determination module includes: a first determination unit, used to determine multiple initial projection area values based on multiple part storage values and multiple part size values; a second determination unit, used to determine multiple target stacking layer numbers of multiple parts based on multiple part properties; a first adjustment unit, used to adjust the initial projection area value of each part according to the target stacking layer number to obtain the target projection area value.

[0015] Optionally, the first determination module also includes: an acquisition unit, used to obtain multiple daily consumption values, multiple parts delivery distances and multiple quality compliance probability values corresponding to multiple parts; a third determination unit, used to determine multiple initial parts reserve values of multiple parts based on the quality compliance probability values, wherein the multiple parts correspond one-to-one to the multiple initial parts reserve values; a second adjustment unit, used to adjust the multiple initial parts reserve values based on the multiple daily consumption values and the multiple parts delivery distances to obtain multiple parts reserve values.

[0016] Optionally, the classification module includes: a fourth determination unit, used to determine, for each part among the multiple parts, an initial part category corresponding to each part according to the target projection area value; a third adjustment unit, used to adjust the initial part category of each part according to the part size value, to obtain the target part category corresponding to each part to obtain a classification result.

[0017] Optionally, the second determination module includes: a fifth determination unit, used to determine multiple storage location areas based on the warehouse size value; an establishment unit, used to establish target correspondences between multiple storage location areas and multiple target part categories; and a sixth determination unit, used to determine the target storage location area for each part based on the target correspondences and the target part categories.

[0018] Optionally, the second determination module also includes: a detection unit, which is used to detect the area occupancy of the target storage area for each part in response to determining the target storage area, and obtain a detection result; a seventh determination unit, which is used to redetermine the target storage area according to the part size value in response to the detection result indicating that the area occupancy is a preset target occupancy.

[0019] According to one embodiment of the present invention, a vehicle is further provided, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute any of the above-mentioned methods for determining a parts storage location.

[0020] According to one embodiment of the present invention, there is also provided an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute any of the above methods for determining a parts location.

[0021] According to one embodiment of the present invention, a non-volatile storage medium is further provided, in which a computer program is stored, wherein the computer program is configured to execute any of the above-mentioned methods for determining a parts location when running.

[0022] In an embodiment of the present invention, multiple part parameters of multiple parts and warehouse size values of a target warehouse are obtained, and multiple target projected area values are determined according to the multiple part parameters, wherein the target projected area value is used to characterize the floor area value of the part, thereby achieving the purpose of classifying multiple parts according to the multiple target projected area values and the multiple part parameters and obtaining the classification results, thereby achieving the technical effect of determining multiple target storage locations of multiple parts according to the warehouse size value and the classification results, wherein the multiple parts correspond one-to-one to the multiple target storage locations, thereby solving the technical problem of low utilization rate of parts storage warehouse locations in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0024] Figure 1 is a flow chart of a method for determining a parts storage location according to one embodiment of the present invention;

[0025] Figure 2 is a schematic diagram of a warehouse parts layout according to one embodiment of the present invention;

[0026] Figure 3 4 is a structural block diagram of a device for determining a parts storage location according to one embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way are interchangeable where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] According to an embodiment of the present invention, an embodiment of a method for determining a parts warehouse location is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system containing at least one set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0030] The method embodiment can also be executed in an electronic device including a memory and a processor, a similar control device, or an in-vehicle terminal. Taking an in-vehicle terminal as an example, the in-vehicle terminal may include one or more processors and a memory for storing data. Optionally, the in-vehicle terminal may also include a communication device and a display device for communication functions. It will be understood by those skilled in the art that the above structural description is only illustrative and does not limit the structure of the in-vehicle terminal. For example, the in-vehicle terminal may also include more or fewer components than those described in the above structural description, or have a configuration different from that described in the above structural description.

[0031] The processor may include one or more processing units. For example, the processor may include a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processing (DSP) chip, a microprocessor, a field-programmable gate array (FPGA), a neural-network processing unit (NPU), a tensor processing unit (TPU), an artificial intelligence (AI) type processor, and the like. Among them, different processing units may be independent components or integrated into one or more processors. In some instances, the electronic device may also include one or more processors.

[0032] The memory can be used to store computer programs, such as a computer program corresponding to the method for determining the parts storage location in an embodiment of the present invention. The processor implements the aforementioned method for determining the parts storage location by executing the computer program stored in the memory. The memory can include high-speed random access memory (RAM) and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory can further include memory remotely located relative to the processor, and these remote memories can be connected to the electronic device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0033] The communication device is used to receive or send data via a grid. Specific examples of the aforementioned grid may include a wireless grid provided by a communication provider of the mobile terminal. In one example, the communication device includes a grid adapter (network interface controller, NIC), which can be connected to other grid devices via a base station to communicate with the Internet. In one example, the communication device can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly. In some embodiments of the present solution, the communication device is used to connect to mobile devices such as mobile phones and tablets, and can send instructions to the vehicle-mounted terminal via the mobile device.

[0034] The display device may be a touchscreen liquid crystal display (LCD) or a touch display (also referred to as a "touch screen" or "touch display"). The LCD may enable a user to interact with the user interface of the vehicle-mounted terminal. In some embodiments, the vehicle-mounted terminal may include a graphical user interface (GUI), and the user may interact with the GUI through finger contacts and / or gestures on the touch-sensitive surface. The human-computer interaction function may include a vehicle gear shifting function, and the executable instructions for executing the human-computer interaction function may be configured / stored in a computer program product or a readable storage medium executable by one or more processors.

[0035] Figure 1 FIG. 1 is a flow chart of a method for determining a parts storage location according to one embodiment of the present invention. Figure 1 As shown, the method includes the following steps:

[0036] Step S102: Acquire multiple part parameters of multiple parts and warehouse size values of the target warehouse.

[0037] Optionally, the execution subject of this embodiment is a parts warehouse location determination system. It should be noted that other electronic devices and processors can also serve as execution subjects, and no further limitations are given here.

[0038] In the technical solution provided in the above step S102 of the present invention, the parts location determination system obtains multiple part parameters of multiple parts to be stored and the warehouse size value of the target warehouse.

[0039] Specifically, the plurality of part parameters include tool dimensions of the part, required inventory of the part, and inherent properties of the part.

[0040] Specifically, the required inventory of these parts can be determined based on the production plan, i.e., the maximum inventory level of each type of parts in stock. In actual operation, the maximum inventory level of parts in the warehouse is generally 100-500. It is worth noting that this maximum inventory level is related to daily parts consumption, the distance to the parts manufacturer, and the quality compliance rate.

[0041] Specifically, by comprehensively evaluating the consumption and supply characteristics of parts, the foresight and flexibility of warehouse planning are achieved, solving the problems of production line stoppages caused by insufficient inventory and the increase in warehousing costs caused by excessive inventory.

[0042] Optionally, when the quality compliance rate of parts is 50%, double the rated quantity of parts needs to be produced to meet the part quantity demand.

[0043] Alternatively, if the daily consumption of a part is 100 pieces, the average supplier transportation time is 3 days, and the quality compliance rate of a large part is 95%, the maximum inventory will be set to cover 4 days of consumption to cope with transportation delays and possible defective products.

[0044] Specifically, the inherent properties of the parts determine the material of the box used to store the parts, such as paper boxes and iron boxes.

[0045] Specifically, the equipment size of a part can be based on the median of the length and width of multiple parts and equipment sizes, and then the storage location size specifications can be anchored upward or downward according to the actual span of the equipment size.

[0046] Step S104 , determining a plurality of target projected area values according to a plurality of part parameters, wherein the target projected area values are used to represent the floor space values of the part.

[0047] In the technical solution provided in the above step S104 of the present invention, the parts storage location determination system determines multiple target projection area values of multiple parts based on the multiple part parameters obtained above, wherein the target projection area value is used to characterize the floor area value of the part. By accurately calculating the number of storage location requirements, this method effectively avoids storage location waste and improves the utilization rate of storage space.

[0048] Specifically, the location projection refers to the vertical projection of a stack of parts. The projected area is related to the number of layers that can be stacked in a full case of parts and the maximum number of parts in stock. It's important to note that decimal places must be rounded up when calculating the projected area of a part.

[0049] For example, if the maximum storage capacity of part A is 10 and the maximum number of layers that can be stacked for the part is 3, then the projected area value of part A is 4 projected areas.

[0050] Step S106 , classifying the multiple parts according to the multiple target projection area values and the multiple part parameters to obtain a classification result.

[0051] In the technical solution provided in the above step S106 of the present invention, the parts location determination system classifies the multiple parts according to the multiple target projection area values and multiple part parameters (part tool dimensions) of the multiple parts to obtain classification results.

[0052] Specifically, the parts storage location system classifies parts of similar sizes among multiple parts into the same category, and then uses the maximum size (i.e., maximum length and width) of multiple parts in this category as the storage location specification of this category. It then defines the storage location specifications of multiple categories of parts, and uses the storage location specification attributes to count the projection requirements of each specification storage location.

[0053] Step S108: determining multiple target storage locations for the multiple parts according to the warehouse size value and the classification result, wherein the multiple parts correspond one-to-one to the multiple target storage locations.

[0054] In the technical solution provided in the above step S108 of the present invention, the parts location determination system determines multiple target locations for placing multiple parts based on the warehouse size value obtained in step S102 and the classification result obtained in step S106, wherein each part has a corresponding target location.

[0055] Specifically, the locations of multiple types of storage location specifications are simulated and planned in the warehouse, and then multiple parts within each storage location specification are placed in the corresponding positions in the warehouse.

[0056] It is worth noting that, considering the human factors in the actual handling process, the size of each storage location in the warehouse should be slightly larger than the actual parts storage location size.

[0057] From the above steps S102 to S108, it can be learned that in the present invention, multiple part parameters of multiple parts and warehouse size values of the target warehouse are obtained, and multiple target projection area values are determined according to the multiple part parameters, wherein the target projection area value is used to characterize the floor area value of the part, thereby achieving the purpose of classifying multiple parts according to the multiple target projection area values and the multiple part parameters to obtain classification results, thereby achieving the technical effect of determining multiple target storage locations of multiple parts according to the warehouse size value and the classification results, wherein the multiple parts correspond one-to-one to the multiple target storage locations, and thus can solve the technical problem of low utilization rate of parts storage warehouse locations in the prior art.

[0058] It's worth noting that existing technologies typically manage large parts using storage yards or shelf storage. Yard storage utilizes floor space, offering lower costs and higher efficiency than shelf storage. However, it presents the following issues: Large backlogs accumulate on the ground, wasting space resources; regular manual inventory checks are time-consuming and labor-intensive, making it difficult to identify safety hazards; parts are susceptible to moisture, rust, and wear; and damaged parts cannot be traced, impacting product quality. Shelf storage, on the other hand, suffers from low space utilization, insufficient storage capacity, and low storage efficiency.

[0059] Compared to existing technologies, the large parts warehouse planning method provided in this application significantly improves warehouse utilization and storage efficiency through precise calculation and scientific classification. It not only effectively manages inventory fluctuations but also flexibly adjusts warehouse layout based on parts consumption and supply characteristics, reducing operator workload, improving logistics speed, and providing solid logistical support for the smooth operation of production processes. This method can significantly reduce warehouse vacancy rates and storage costs, while also improving the accuracy of parts retrieval and extraction and reducing production downtime, resulting in significant economic and management benefits.

[0060] The above method of this embodiment is further described in detail below.

[0061] As an optional implementation, the multiple part parameters include part reserve values, part size values and part attributes. Determining multiple target projection area values based on the multiple part parameters includes: determining multiple initial projection area values based on the multiple part reserve values and the multiple part size values; determining multiple target stacking layer numbers of the multiple parts based on the multiple part attributes; and adjusting the initial projection area value of each part based on the target stacking layer number to obtain the target projection area value.

[0062] In this embodiment, determining multiple target projection area values based on multiple part parameters includes the following steps: for each part among the multiple parts, determining the initial projection area value of the part based on the part storage value and the part size value of the part, then determining the maximum number of layers that can be stacked for the part based on the part properties of the part, and adjusting the initial projection area value of the part based on the above-mentioned maximum number of layers that can be stacked, and finally obtaining the target projection area value.

[0063] Specifically, the above-mentioned part parameters include part inventory value, part size value and part attributes.

[0064] Specifically, in a ground stacking scenario, the projected storage location requirement is calculated based on the number of layers of a full case of large parts and equipment. This reflects the actual storage location requirements based on the vertical projection area of a single stack. For example, if the required inventory of a large part is 400 pieces and each equipment can be stacked four layers in a full case, the required storage location is 100.

[0065] Specifically, by accurately calculating the number of required storage locations, we can effectively avoid wasted storage space and improve storage space utilization. It's worth noting that this method applies to various storage environments, including but not limited to ground stacking scenarios, such as high-bay racking and automated warehouses. By adjusting the calculation parameters, we can achieve flexibility and efficiency in storage location planning.

[0066] As an optional implementation, the method also includes: obtaining multiple daily consumption values, multiple parts delivery distances and multiple quality compliance probability values corresponding to multiple parts; determining multiple initial parts reserve values for the multiple parts based on the quality compliance probability values, wherein the multiple parts correspond one-to-one to the multiple initial parts reserve values; adjusting the multiple initial parts reserve values based on the multiple daily consumption values and the multiple parts delivery distances to obtain multiple parts reserve values.

[0067] In this embodiment, determining the target parts reserve value of a part includes the following steps: for each part among a plurality of parts, the parts warehouse location determination system obtains the daily consumption value, parts delivery distance and quality compliance probability value corresponding to each part, and then determines the initial parts reserve value of the part based on the quality compliance probability value of the part, and further adjusts the initial parts reserve value of the part based on the daily consumption value of the part and the parts delivery distance to obtain the target parts reserve value.

[0068] Specifically, the target part inventory level is tied to key factors such as daily part consumption, average supplier delivery time, and part quality compliance. This ensures that the production line can continue operating even in unforeseen circumstances, such as supplier delivery delays. For example, for a large part with a daily consumption of 100 units, an average supplier delivery time of three days, and a quality compliance rate of 95%, the maximum inventory level would be set to cover four days of consumption, to account for delivery delays and potential defective parts.

[0069] Specifically, by comprehensively evaluating the consumption and supply characteristics of parts, this method achieves forward-looking and flexible inventory planning, resolving issues such as production line downtime caused by insufficient inventory and increased storage costs caused by excessive inventory. It's worth noting that this method isn't limited to large parts; it can also be applied to inventory planning for various types of parts, including small and medium-sized items, ensuring stability and efficiency across the entire supply chain.

[0070] As an optional implementation, multiple parts are classified according to multiple target projection area values and multiple part parameters to obtain a classification result, including: for each part of the multiple parts, determining an initial part category corresponding to each part according to the target projection area value; adjusting the initial part category of each part according to the part size value to obtain the target part category corresponding to each part to obtain a classification result.

[0071] In this embodiment, the parts warehouse location determination system classifies multiple parts according to the target projected area value and part parameters of the parts, and obtains the classification results including the following steps: for each part of the multiple parts, determine the initial part category to which the part belongs according to the target projected area value of the part, and then further adjust the initial part category of the part according to the part size value of the part to obtain the target part category corresponding to the part.

[0072] Specifically, multiple parts are categorized by size to facilitate unified warehouse planning. For example, multiple parts can be categorized into three sizes: small (less than 2 meters in length and width), medium (2 to 5 meters), and large (greater than 5 meters).

[0073] Specifically, categorizing by size and specification facilitates standardized storage design, reduces the complexity of storage planning, and improves the rationality of storage layout. It's worth noting that the size and specification classification method is not limited to the examples above. Classification criteria can be flexibly adjusted based on the specific storage environment and part characteristics, including but not limited to classification by weight, shape, material, and more, to meet more complex and changing storage needs.

[0074] As an optional implementation, determining multiple target storage locations for multiple parts based on warehouse size values and classification results includes: determining multiple storage location areas based on warehouse size values; establishing target correspondences between multiple storage location areas and multiple target part categories; and determining the target storage location area for each part based on the target correspondences and the target part categories.

[0075] In this embodiment, the parts location determination system can determine multiple target locations of multiple parts based on the warehouse size value and the classification results obtained in the above steps, including the following steps: the parts location system determines multiple location areas in the warehouse based on the warehouse size value of the target warehouse, and then establishes a correspondence between the above multiple location areas and multiple target part categories, and determines the target location area of each part through the established correspondence and the target part categories of the multiple parts.

[0076] Specifically, we use simulations to plan warehouse locations and make adjustments based on the results to optimize warehouse planning. For example, we first determine the minimum width requirements for operating aisles, then perform a preliminary layout based on statistical data on warehouse specifications. Finally, we optimize the location and size of the shelves based on the results of the layout. Simulations and adjustments ensure the rationality of warehouse planning, improve warehouse operation efficiency, and reduce logistics delays caused by inappropriate layouts.

[0077] Specifically, such as Figure 2 As shown, based on the finalized storage layout plan determined in the simulation layout and adjustment steps, the actual storage layout is implemented. During the system maintenance step, the storage planning system is maintained to ensure its continued efficient operation. For example, in a ground stacking scenario, the depth of the storage grid is designed to be limited to no more than 5 units based on the frequency of batch switching for large parts, improving storage operation efficiency.

[0078] Optional system maintenance includes but is not limited to regular location attribute verification, part information updates, warehousing rule adjustments, etc., to ensure that the location planning system can adapt to changes in production demand, continuously optimize warehouse management, reduce staff labor intensity, improve logistics speed, and provide solid logistical support for the smooth operation of the production process.

[0079] Optionally, the simulated layout can use tools including but not limited to computer-aided design (CAD), warehouse management software (WMS), etc., to achieve optimization of warehouse location planning through repeated testing and optimization in a virtual environment. At the same time, the flexibility of the simulated layout allows for rapid adjustments in actual operations to cope with sudden inventory fluctuations.

[0080] Specifically, based on the number of storage location requirements obtained in the calculation steps, the total storage location requirements for each size specification are calculated. For example, if the storage location specification attributes are defined in the warehousing system, the statistical results show that the number of small storage locations required is 300, the number of medium storage locations required is 200, and the number of large storage locations required is 100.

[0081] Specifically, this method provides a quantitative basis for warehouse location planning, ensuring the scientific and practical nature of warehouse layout. It's worth noting that warehouse location demand statistics aren't limited to size specifications; they can also incorporate characteristics like part usage frequency and seasonal demand, enabling more detailed warehouse location demand analysis to achieve optimal allocation of warehouse resources.

[0082] As an optional embodiment, the method also includes: for each part, in response to determining the target storage location area, detecting the area occupancy of the target storage location area to obtain a detection result; in response to the detection result indicating that the area occupancy is a preset target occupancy, re-determining the target storage location area according to the part size value.

[0083] In this embodiment, the above method also includes the following steps: for each part, after determining the target storage area of the part, it is also necessary to detect the area occupancy of the target storage area corresponding to the part to obtain a detection result. When the detection result shows that the area occupancy rate is 100%, the part storage location determination system needs to re-determine the target storage area corresponding to the part based on the part size value of the part.

[0084] Specifically, within the warehouse management system, location attributes are linked to part information, and warehousing rules based on part attributes are developed. Locations that match part specifications are prioritized. If matching locations are insufficient, the parts are automatically allocated to larger locations until a suitable placement is found. For example, for large parts measuring 2m x 2m x 2m, medium locations are prioritized. If medium locations are insufficient, large locations are automatically allocated, ensuring timely part placement.

[0085] Specifically, through automated warehousing rules, this method reduces human errors in warehouse allocation, improves warehousing efficiency, and ensures the rational use of warehouse space.

[0086] Through the description of the above embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus the necessary general hardware platform, or of course by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or grid device, etc.) to execute the methods of various embodiments of the present invention.

[0087] This embodiment also provides a device for determining the location of a parts warehouse, which is used to implement the above-mentioned embodiments and preferred embodiments. Details that have already been described will not be repeated. As used below, the term "module" may refer to a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0088] Figure 3 FIG. 3 is a structural block diagram of a device 300 for determining a parts storage location according to one embodiment of the present invention. Figure 3 As shown, the device includes: an acquisition module 301 , a first determination module 302 , a classification module 303 and a second determination module 304 .

[0089] An acquisition module 301 is used to acquire a plurality of part parameters of a plurality of parts and a warehouse size value of a target warehouse;

[0090] A first determining module 302 is configured to determine a plurality of target projected area values based on a plurality of part parameters, wherein the target projected area values are used to represent the footprint values of the part;

[0091] A classification module 303 is used to classify multiple parts according to multiple target projection area values and multiple part parameters to obtain a classification result;

[0092] The second determining module 304 is configured to determine a plurality of target storage locations for the plurality of parts according to the warehouse size value and the classification result, wherein the plurality of parts correspond to the plurality of target storage locations in a one-to-one manner.

[0093] Optionally, the acquisition module 301 includes: a first acquisition unit for acquiring real-time vehicle-mounted images; a first determination unit for determining a first resolution of the real-time vehicle-mounted image; a comparison unit for comparing the first resolution with a preset resolution; and a second determination unit for determining that the real-time vehicle-mounted image is a vehicle-mounted image to be processed in response to the first resolution being less than the preset resolution.

[0094] Optionally, the first determination module 302 includes: a first determination unit, used to determine multiple initial projected area values based on multiple part storage values and multiple part size values; a second determination unit, used to determine multiple target stacking layer numbers of multiple parts based on multiple part attributes; a first adjustment unit, used to adjust the initial projected area value of each part according to the target stacking layer number to obtain the target projected area value.

[0095] Optionally, the first determination module 302 also includes: an acquisition unit, used to obtain multiple daily consumption values, multiple parts delivery distances and multiple quality compliance probability values corresponding to multiple parts; a third determination unit, used to determine multiple initial parts reserve values of multiple parts based on the quality compliance probability values, wherein the multiple parts correspond one-to-one to the multiple initial parts reserve values; a second adjustment unit, used to adjust the multiple initial parts reserve values based on the multiple daily consumption values and the multiple parts delivery distances to obtain multiple parts reserve values.

[0096] Optionally, the classification module 303 includes: a fourth determination unit, used to determine, for each part among the multiple parts, an initial part category corresponding to each part according to the target projection area value; a third adjustment unit, used to adjust the initial part category of each part according to the part size value, to obtain the target part category corresponding to each part to obtain a classification result.

[0097] Optionally, the second determination module 304 includes: a fifth determination unit, used to determine multiple storage location areas based on the warehouse size value; an establishment unit, used to establish target correspondences between multiple storage location areas and multiple target part categories; and a sixth determination unit, used to determine the target storage location area for each part based on the target correspondences and the target part categories.

[0098] Optionally, the second determination module 304 also includes: a detection unit, which is used to detect the area occupancy of the target storage area for each part in response to determining the target storage area, and obtain a detection result; a seventh determination unit, which is used to redetermine the target storage area according to the part size value in response to the detection result indicating that the area occupancy is a preset target occupancy.

[0099] An embodiment of the present invention further provides a vehicle, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the above-mentioned method for determining the parts storage location.

[0100] Optionally, in this embodiment, the vehicle may be configured to store a computer program for performing the following steps:

[0101] Step S102, obtaining multiple part parameters of multiple parts and warehouse size values of the target warehouse;

[0102] Step S104, determining a plurality of target projected area values according to a plurality of part parameters, wherein the target projected area values are used to represent the floor space values of the part;

[0103] Step S106, classifying the multiple parts according to the multiple target projection area values and the multiple part parameters to obtain a classification result;

[0104] Step S108: determining multiple target storage locations for the multiple parts according to the warehouse size value and the classification result, wherein the multiple parts correspond one-to-one to the multiple target storage locations.

[0105] Optionally, when executing the program, the processor further implements the following steps: determining multiple initial projected area values based on multiple part storage values and multiple part size values; determining multiple target stacking layer numbers of multiple parts based on multiple part attributes; and adjusting the initial projected area value of each part based on the target stacking layer number to obtain a target projected area value.

[0106] Optionally, when executing the program, the processor also implements the following steps: obtaining multiple daily consumption values, multiple parts delivery distances and multiple quality compliance probability values corresponding to multiple parts; determining multiple initial parts reserve values for the multiple parts based on the quality compliance probability values, wherein the multiple parts correspond one-to-one to the multiple initial parts reserve values; adjusting the multiple initial parts reserve values based on the multiple daily consumption values and the multiple parts delivery distances to obtain multiple parts reserve values.

[0107] Optionally, when executing the program, the processor further implements the following steps: for each part among the multiple parts, determining the initial part category corresponding to each part based on the target projection area value; adjusting the initial part category of each part based on the part size value to obtain the target part category corresponding to each part to obtain a classification result.

[0108] Optionally, when executing the program, the processor also implements the following steps: determining multiple storage location areas based on warehouse size values; establishing target correspondences between multiple storage location areas and multiple target part categories; and determining the target storage location area for each part based on the target correspondences and the target part categories.

[0109] Optionally, the processor also implements the following steps when executing the program: for each part, in response to determining the target storage location area, the area occupancy of the target storage location area is detected to obtain a detection result; in response to the detection result indicating that the area occupancy is a preset target occupancy, the target storage location area is re-determined according to the part size value.

[0110] Optionally, specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0111] An embodiment of the present invention further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the above-mentioned method for determining the parts storage location.

[0112] Optionally, in this embodiment, the electronic device may be configured to store a computer program for performing the following steps:

[0113] Step S102, obtaining multiple part parameters of multiple parts and warehouse size values of the target warehouse;

[0114] Step S104, determining a plurality of target projected area values according to a plurality of part parameters, wherein the target projected area values are used to represent the floor space values of the part;

[0115] Step S106, classifying the multiple parts according to the multiple target projection area values and the multiple part parameters to obtain a classification result;

[0116] Step S108: determining multiple target storage locations for the multiple parts according to the warehouse size value and the classification result, wherein the multiple parts correspond one-to-one to the multiple target storage locations.

[0117] Optionally, when executing the program, the processor further implements the following steps: determining multiple initial projected area values based on multiple part storage values and multiple part size values; determining multiple target stacking layer numbers of multiple parts based on multiple part attributes; and adjusting the initial projected area value of each part based on the target stacking layer number to obtain a target projected area value.

[0118] Optionally, when executing the program, the processor also implements the following steps: obtaining multiple daily consumption values, multiple parts delivery distances and multiple quality compliance probability values corresponding to multiple parts; determining multiple initial parts reserve values for the multiple parts based on the quality compliance probability values, wherein the multiple parts correspond one-to-one to the multiple initial parts reserve values; adjusting the multiple initial parts reserve values based on the multiple daily consumption values and the multiple parts delivery distances to obtain multiple parts reserve values.

[0119] Optionally, when executing the program, the processor further implements the following steps: for each part among the multiple parts, determining the initial part category corresponding to each part based on the target projection area value; adjusting the initial part category of each part based on the part size value to obtain the target part category corresponding to each part to obtain a classification result.

[0120] Optionally, when executing the program, the processor also implements the following steps: determining multiple storage location areas based on warehouse size values; establishing target correspondences between multiple storage location areas and multiple target part categories; and determining the target storage location area for each part based on the target correspondences and the target part categories.

[0121] Optionally, the processor also implements the following steps when executing the program: for each part, in response to determining the target storage location area, the area occupancy of the target storage location area is detected to obtain a detection result; in response to the detection result indicating that the area occupancy is a preset target occupancy, the target storage location area is re-determined according to the part size value.

[0122] Optionally, specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0123] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is configured to execute the above-mentioned method for determining the parts location when running on a computer or a processor.

[0124] Optionally, in this embodiment, the computer-readable storage medium may be configured to store a computer program for performing the following steps:

[0125] Step S102, obtaining multiple part parameters of multiple parts and warehouse size values of the target warehouse;

[0126] Step S104, determining a plurality of target projected area values according to a plurality of part parameters, wherein the target projected area values are used to represent the floor space values of the part;

[0127] Step S106, classifying the multiple parts according to the multiple target projection area values and the multiple part parameters to obtain a classification result;

[0128] Step S108: determining multiple target storage locations for the multiple parts according to the warehouse size value and the classification result, wherein the multiple parts correspond one-to-one to the multiple target storage locations.

[0129] Optionally, the storage medium is configured to store program code for performing the following steps: determining multiple initial projected area values based on multiple part reserve values and multiple part size values; determining multiple target stacking layer numbers of multiple parts based on multiple part attributes; and adjusting the initial projected area value of each part based on the target stacking layer number to obtain a target projected area value.

[0130] Optionally, the storage medium is configured to store program code for executing the following steps: obtaining multiple daily consumption values, multiple parts delivery distances, and multiple quality compliance probability values corresponding to multiple parts; determining multiple initial parts reserve values for the multiple parts based on the quality compliance probability values, wherein the multiple parts correspond one-to-one to the multiple initial parts reserve values; adjusting the multiple initial parts reserve values based on the multiple daily consumption values and the multiple parts delivery distances to obtain multiple parts reserve values.

[0131] Optionally, the storage medium is configured to store program code for performing the following steps: for each part of a plurality of parts, determining an initial part category corresponding to each part based on a target projected area value; adjusting the initial part category of each part based on a part size value to obtain a target part category corresponding to each part to obtain a classification result.

[0132] Optionally, the storage medium is configured to store program code for performing the following steps: determining multiple storage location areas based on warehouse dimension values; establishing target correspondences between multiple storage location areas and multiple target part categories; and determining a target storage location area for each part based on the target correspondences and the target part categories.

[0133] Optionally, the storage medium is configured to store program code for performing the following steps: for each part, in response to determining the target storage location area, the area occupancy of the target storage location area is detected to obtain a detection result; in response to the detection result indicating that the area occupancy is a preset target occupancy, the target storage location area is re-determined according to the part size value.

[0134] Optionally, specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0135] An embodiment of the present invention further provides a computer program product, comprising a computer program, wherein the computer program implements the steps of the above-mentioned method for determining the parts storage location when executed by a processor.

[0136] Optionally, in this embodiment, the computer program product may be configured to store a computer program for performing the following steps:

[0137] Step S102, obtaining multiple part parameters of multiple parts and warehouse size values of the target warehouse;

[0138] Step S104, determining a plurality of target projected area values according to a plurality of part parameters, wherein the target projected area values are used to represent the floor space values of the part;

[0139] Step S106, classifying the multiple parts according to the multiple target projection area values and the multiple part parameters to obtain a classification result;

[0140] Step S108: determining multiple target storage locations for the multiple parts according to the warehouse size value and the classification result, wherein the multiple parts correspond one-to-one to the multiple target storage locations.

[0141] Optionally, when the computer program is executed, the following steps are also implemented: multiple initial projected area values are determined based on multiple part storage values and multiple part size values; multiple target stacking layer numbers of multiple parts are determined based on multiple part properties; and the initial projected area value of each part is adjusted based on the target stacking layer number to obtain the target projected area value.

[0142] Optionally, when the computer program is executed, the following steps are also implemented: obtaining multiple daily consumption values, multiple parts delivery distances and multiple quality compliance probability values corresponding to multiple parts; determining multiple initial parts reserve values for the multiple parts based on the quality compliance probability values, wherein the multiple parts correspond one-to-one to the multiple initial parts reserve values; adjusting the multiple initial parts reserve values based on the multiple daily consumption values and the multiple parts delivery distances to obtain multiple parts reserve values.

[0143] Optionally, when the computer program is executed, the following steps are further implemented: for each part among the multiple parts, an initial part category corresponding to each part is determined based on the target projected area value; the initial part category of each part is adjusted based on the part size value to obtain the target part category corresponding to each part to obtain a classification result.

[0144] Optionally, when the computer program is executed, the following steps are also implemented: determining multiple storage location areas based on warehouse size values; establishing target correspondences between multiple storage location areas and multiple target part categories; and determining the target storage location area for each part based on the target correspondences and the target part categories.

[0145] Optionally, the computer program further implements the following steps when executing the program: for each part, in response to determining the target storage location area, the area occupancy of the target storage location area is detected to obtain a detection result; in response to the detection result indicating that the area occupancy is a preset target occupancy, the target storage location area is re-determined according to the part size value.

[0146] Optionally, specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0147] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0148] In some embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0149] Units described as separate components may or may not be physically separate, and 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 may be selected to achieve the purpose of the present embodiment according to actual needs.

[0150] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0151] If the integrated unit is implemented in the form of 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 the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or grid device, etc.) to execute all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc., various media that can store program code.

[0152] The above are only preferred embodiments of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for determining a parts storage location, characterized in that: include: Obtain multiple part parameters of multiple parts and warehouse size values of a target warehouse; Determining a plurality of target projected area values according to the plurality of part parameters, wherein the target projected area values are used to represent the floor space values of the part; Classifying the multiple parts according to the multiple target projection area values and the multiple part parameters to obtain a classification result; A plurality of target storage locations of the plurality of parts are determined according to the warehouse size value and the classification result, wherein the plurality of parts correspond one-to-one to the plurality of target storage locations.

2. The method for determining the parts storage location according to claim 1, characterized in that: The plurality of part parameters include part stock values, part size values, and part attributes. Determining the plurality of target projected area values based on the plurality of part parameters includes: Determining a plurality of initial projected area values according to a plurality of the part reserve values and a plurality of the part size values; Determining a plurality of target stacking layers of the plurality of parts according to a plurality of part attributes; According to the target number of stacking layers, the initial projected area value of each part is adjusted to obtain the target projected area value.

3. The method for determining the parts storage location according to claim 2, characterized in that: The method further comprises: Obtaining multiple daily consumption values, multiple parts delivery distances, and multiple quality compliance probability values corresponding to the multiple parts; Determining a plurality of initial parts reserve values for the plurality of parts according to the quality compliance probability values, wherein the plurality of parts correspond one to one to the plurality of initial parts reserve values; The multiple initial parts reserve values are adjusted according to the multiple daily consumption values and the multiple parts delivery distances to obtain the multiple parts reserve values.

4. The method for determining the parts storage location according to claim 2, characterized in that: Classifying the multiple parts according to the multiple target projection area values and the multiple part parameters, and obtaining the classification result includes: For each of the plurality of parts, determining an initial part category corresponding to each part according to the target projected area value; The initial part category of each part is adjusted according to the part size value to obtain the target part category corresponding to each part to obtain the classification result.

5. The method for determining the parts storage location according to claim 4, characterized in that: Determining the plurality of target storage locations of the plurality of parts according to the warehouse size value and the classification result includes: determining a plurality of storage location areas according to the warehouse size value; Establishing target correspondences between the plurality of storage location areas and the plurality of target part categories; The target storage area of each part is determined according to the target correspondence relationship and the target part category.

6. The method for determining the parts storage location according to claim 5, characterized in that: The method further comprises: For each part, in response to determining the target storage area, detecting the area occupancy of the target storage area to obtain a detection result; In response to the detection result indicating that the area occupancy rate is a preset target occupancy rate, the target storage location area is re-determined according to the part size value.

7. A device for determining a parts storage location, characterized in that: Applied to a device-side communication test system, the device comprises: An acquisition module, used for acquiring multiple part parameters of multiple parts and warehouse size values of a target warehouse; a first determining module, configured to determine a plurality of target projected area values according to the plurality of part parameters, wherein the target projected area values are used to represent the floor space values of the part; a classification module, configured to classify the plurality of parts according to the plurality of target projection area values and the plurality of part parameters to obtain a classification result; The second determining module is used to determine multiple target storage locations of the multiple parts according to the warehouse size value and the classification result, wherein the multiple parts correspond to the multiple target storage locations one by one.

8. An electronic device comprising a memory and a processor, characterized in that: The memory stores a computer program, and the processor is configured to run the computer program to execute the method for determining the parts storage location as claimed in any one of claims 1 to 6.

9. A vehicle comprising a memory and a processor, characterized in that: The memory stores a computer program, and the processor is configured to run the computer program to execute the method for determining the parts storage location as claimed in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein the computer program is configured to execute the method for determining the parts location according to any one of claims 1 to 6 when running on a computer or a processor.

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