Appliance non-fixed slot position frame matching method and device and storage medium

Abstract

The invention discloses an appliance non-fixed slot position frame matching method and device and a storage medium. The method comprises the steps that production task data used for producing automobile parts are acquired, and the production task data comprise production plan data, assembly plan data and material serial number information; determining target material identification data based on the production task data; based on the target material identification data, a target slot position frame matching mode is determined, and the target slot position frame matching mode is used for placing a target material to a target slot position; and on the basis of the target slot position frame matching mode, a control instruction set is generated, and the control instruction set is used for controlling a mechanical arm execution end to place the target material to the target slot position. By adopting the automatic and data-driven logistics sorting process, the logistics efficiency can be remarkably improved, the cost can be reduced, meanwhile, the continuity and high-efficiency operation of a production line are guaranteed, and the technical problem that the overall efficiency is low in the existing logistics sorting process is solved.

Description

Technical Field

[0001] The present invention relates to intelligent logistics equipment technology, and in particular to a method, device and storage medium for non-fixed slot racking of equipment. Background Art

[0002] In modern manufacturing, picking bridges the gap between inventory and production lines, with its efficiency and accuracy directly impacting the smoothness of the entire production process. However, traditional picking often relies on manual sorting and processing, which not only increases time costs but also frequently leads to sorting errors, severely impacting production line efficiency and driving up logistics costs.

[0003] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0004] The embodiments of the present invention provide a method, device and storage medium for non-fixed slot racking of appliances, so as to at least solve the technical problem of low overall efficiency of the existing logistics picking process.

[0005] According to one aspect of an embodiment of the present invention, in order to achieve the above-mentioned purpose, according to one aspect of the present invention, a method for arranging a non-fixed slot of an appliance is provided, comprising:

[0006] Acquire production task data for producing automotive parts, wherein the production task data includes: production plan data, assembly plan data, and material serial number information; determine target material identification data based on the production task data; determine a target slot matching mode based on the target material identification data, wherein the target slot matching mode is used to place the target material in the target slot; generate a control instruction set based on the target slot matching mode, wherein the control instruction set is used to control the robotic arm execution end to place the target material in the target slot.

[0007] Furthermore, based on the production task data, the target material identification data is determined, including: based on the production task data, determining the target material list data; based on the material basic data, determining the target material identification data according to the target material list data; wherein the material basic data at least includes: part type data, instrument type data and instrument and part relationship data, wherein the part type data at least includes: recycled standardized containers, global logistics type containers and special logistics type containers, the instrument type data at least includes: standard instruments and non-standard instruments, and the instrument and part relationship data at least includes: the correspondence between instruments and parts and carrying capacity information.

[0008] Furthermore, based on the material basic data and according to the target material list data, the target material identification data is determined, including: based on the material basic data and the target material list data, the target storage type data, the material usage frequency data and the target instrument type data are determined; based on the target storage type data, the material usage frequency data and the target instrument type data, the target optimal slot data is determined; based on the target optimal slot data, the target racking data is determined, wherein the target racking data includes at least: racking order number data, production process data, instrument order number and material list data; based on the logistics template data, according to the target racking data, the corresponding target material identification data is determined.

[0009] Furthermore, based on the target storage type data, material usage frequency data and target equipment type data, the target optimal slot data is determined, including: based on the target storage type data and material usage frequency data, the target material storage requirement data and the load requirement data are determined, wherein the target material storage requirement data at least includes: storage temperature data, storage humidity data, storage shockproof level and storage anti-static level; based on the slot placement status history database, the target material storage requirement data, the load requirement data and the target equipment type data, the target optimal slot data is determined.

[0010] Furthermore, based on the target material identification data, the target slot matching mode is determined, including: determining the target robotic arm model based on the target material identification data; determining the robotic arm path data based on the target robotic arm model; and determining the target slot matching mode based on the robotic arm path data.

[0011] Furthermore, based on the target material identification data, the target robotic arm model is determined, including: based on the target material identification data, determining the target tool position and the target material grasping method; based on the current idle robotic arm position data, determining the target robotic arm model according to the target tool position and the target material grasping method.

[0012] Furthermore, after generating the control instruction set based on the target slot configuration mode, the method further includes: storing the storage status of the current target slot in a slot placement status history database.

[0013] According to one embodiment of the present invention, there is also provided an apparatus for non-fixed slot matching, comprising: an acquisition module for acquiring production task data for producing automotive parts, wherein the production task data comprises production plan data, assembly plan data and material serial number information; an identification module for determining target material identification data based on the production task data; a matching module for determining a target slot matching mode based on the target material identification data, wherein the target slot matching mode is used to place the target material in the target slot; a control module for generating a control instruction set based on the target slot matching mode, wherein the control instruction set is used to control the robotic arm execution end to place the target material in the target slot.

[0014] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0015] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0016] In an embodiment of the present invention, production task data is obtained by responding to production scheduling instructions, target material identification data is determined based on the production task data, and a target slot matching mode is determined based on the target material identification data. The target slot matching mode is used to place the target material in the target slot. Based on the target slot matching mode, a control instruction set is generated. The control instruction set is used to control the robotic arm execution end to place the target material in the corresponding target slot. By adopting an automated and data-driven logistics picking process, it is achieved that logistics efficiency can be significantly improved and costs can be reduced, while ensuring the continuity and high-efficiency operation of the production line, thereby solving the technical problem of low overall efficiency of the existing logistics picking process. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] 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:

[0018] Figure 1 This is a flow chart of a method for arranging equipment in non-fixed slots according to one embodiment of the present invention;

[0019] Figure 2 This is a flow chart of another method for arranging non-fixed slots of appliances according to one embodiment of the present invention;

[0020] Figure 3The present invention is a block diagram of a non-fixed slot mounting device for an appliance according to one embodiment of the present invention. DETAILED DESCRIPTION

[0021] 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.

[0022] 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 numbers used in this way can be interchanged 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.

[0023] According to an embodiment of the present invention, a method embodiment of a method for non-fixed slot racking of an instrument is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a 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.

[0024] The method embodiment can be executed in an electronic device or similar computing device that includes a memory and a processor. Taking running on a vehicle terminal as an example, the vehicle terminal may include one or more processors (processors may include but are not limited to central processing units (CPUs), graphics processing units (GPUs), digital signal processing (DSP) chips, microcontroller units (MCUs), field programmable gate arrays (FPGAs), neural network processors (NPUs), tensor processing units (TPUs), artificial intelligence (AI) type processors, etc.) and a memory for storing data. Optionally, the vehicle terminal may also include transmission equipment, input and output equipment, and display equipment for communication functions. Those skilled in the art will understand that the above structural description is only illustrative and does not limit the structure of the vehicle terminal. For example, the vehicle terminal may also include more or fewer components than those described above, or have a configuration different from that described above.

[0025] The memory can be used to store computer programs, such as software programs and modules of application software, such as the computer program corresponding to the method for non-fixed slot configuration of devices in the embodiments of the present invention. The processor executes the computer program stored in the memory to perform various functional applications and data processing, thereby implementing the above-mentioned method for non-fixed slot configuration of devices. The memory can include high-speed random access memory 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 may further include memory remotely located relative to the processor, and these remote memories can be connected to the mobile terminal 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.

[0026] The transmission device is used to receive or send data via a network. Specific examples of the aforementioned network may include a wireless network provided by the mobile terminal's communications provider. In one embodiment, the transmission device includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In one embodiment, the transmission device may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0027] The display device can be, for example, a touch-screen liquid crystal display (LCD) and a touch display (also referred to as a "touch screen" or "touch display screen"). The liquid crystal display can enable the user to interact with the user interface of the mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GUI), and the user can interact with the GUI by finger contacts and / or gestures on the touch-sensitive surface. The human-computer interaction functions here optionally include the following interactions: creating web pages, drawing, word processing, making electronic documents, games, video conferencing, instant messaging, sending and receiving emails, call interfaces, playing digital videos, playing digital music and / or web browsing, etc. The executable instructions for performing the above-mentioned human-computer interaction functions are configured / stored in a computer program product or readable storage medium executable by one or more processors.

[0028] Figure 1 FIG. 1 is a flow chart of a method for arranging a non-fixed slot for an appliance according to one embodiment of the present invention. Figure 1 As shown, the method includes the following steps:

[0029] Step S10, obtaining production task data for producing automobile parts, wherein the production task data includes: production plan data, assembly plan data and material serial number information;

[0030] In step S10, production planning data is developed by company management based on market demand, inventory status, and production capacity. It includes key information such as the expected product type, quantity, and projected start and end dates. This includes the specific models and specifications of the automotive parts to be produced, as well as the production start and end dates based on sales forecasts and inventory requirements, and the planned timeframes for each phase.

[0031] Assembly planning data is more specific, detailing the steps and processes for assembling various components into the final product. This data typically comes from production management or dedicated production planning and control software. It primarily includes the assembly sequence, assembly process, and human and equipment resource requirements.

[0032] Material serial numbers, often referred to as tracking numbers or serial numbers, are unique identifiers for each individual part. In automotive manufacturing, they are not only used to track the material's origin, status, and location, but are also crucial for ensuring part quality and traceability. These include material coding, serial number generation logic, and the material lifecycle.

[0033] In step S10, obtaining production task data is a dynamic, multi-step process, mainly including:

[0034] Real-time interface call: Real-time connection with ERP, supply chain management and other production planning software through API interface, automatically downloading the latest production planning data and assembly planning data.

[0035] Data integration and cleaning: After receiving the raw data, necessary data cleaning and format conversion are performed to ensure data consistency and integrity and prepare for subsequent processing.

[0036] Serial number information matching: Based on the parts requirements specified in the production plan data, the corresponding material serial number information is obtained through database query or barcode / RFID scanning technology to ensure that each batch of materials can be correctly identified and tracked.

[0037] Cross-validation and updating: Cross-validation between production plan data and assembly plan data, as well as comparison with the actual status of materials, can identify and correct potential data inconsistencies or errors, ensuring the accuracy of production instructions.

[0038] Generate a production task list: Convert the cleaned and organized data into a specific production task list, including the production quantity of each component, assembly sequence, and serial number information of the required materials, as the basis for the next step of operation.

[0039] Through the detailed production task data acquisition process described above, manufacturers can accurately guide logistics picking, production scheduling, and assembly line operations, ensuring that each production activity can be executed efficiently and accurately, meeting market demand while maintaining production flexibility and traceability.

[0040] Step S20, determining target material identification data based on the production task data;

[0041] In step S20, determining the target material identification data based on the production task data is a key step in achieving efficient material distribution and accurate racking. This process involves multi-level data analysis and matching to ensure the correct selection and allocation of materials, specifically including:

[0042] Based on the received production task data, namely the production plan, assembly requirements, and material serial number information, the specific parts list required for this production run is parsed. The names, quantities, and specifications of all parts to be processed are listed to form the target bill of materials data, which serves as the basis for subsequent material identification data determination. Basic material data covers part types (such as reusable standardized containers, global logistics type containers, and special logistics type containers), instrument types (such as standard instruments and non-standard instruments), their corresponding relationships, and carrying capacity information.

[0043] Combined with the simultaneously acquired target bill of materials data, the most appropriate material identification data will be automatically matched to ensure that each part is accompanied by a unique and appropriate identification for subsequent tracking and management.

[0044] Based on the above foundation, the specific process for determining target material identification data is as follows: The target storage type data (such as temperature, humidity, shock resistance, and anti-static level requirements) and material usage frequency data in the material basic data are combined to comprehensively evaluate the storage and usage characteristics of each material. This step aims to optimize the material storage environment and accessibility, providing a basis for subsequent slot allocation.

[0045] Based on the material's storage requirements, usage frequency, and target equipment type data, an algorithm calculates the ideal storage slot for each material. The optimal target slot data is determined, taking into account safe storage conditions, easy access, and efficient use of equipment space.

[0046] Once the optimal target slot location is determined, target racking data is generated, including the racking order number, production process, instrument number, and bill of materials. Each racking data item serves as a detailed guide for material distribution for a specific production task, ensuring accurate and efficient logistics distribution from the warehouse to the production site. Finally, the pre-defined logistics template data is combined with the target racking data to determine the final material identification data.

[0047] In order to more accurately determine the optimal slot location, further consideration is needed: matching material storage requirements with carrying capacity:

[0048] Based on the material's storage requirements (such as temperature, humidity, shockproofing, and anti-static requirements) and the actual carrying capacity of the equipment, ensure that materials are stored under appropriate conditions while avoiding overloading or wasting space. Utilizing a historical database of slot placement status, combined with current material storage requirements, carrying requirements, and target equipment information, we can learn from past best practices and provide smarter, more personalized recommendations for slot allocation under new tasks. Through this series of analysis and decision-making processes, we ensure that materials for each production task are accurately identified, efficiently racked, and precisely delivered, significantly improving the efficiency and accuracy of production logistics while also reducing errors and costs associated with manual operations.

[0049] Step S40: determining a target slot allocation mode based on the target material identification data, wherein the target slot allocation mode is used to place the target material into the target slot;

[0050] In step S40, the precise operation of the robotic arm is the core of material racking and delivery. Determining the target slot racking mode based on the target material identification data not only optimizes the material handling process, but also significantly improves production efficiency and accuracy. The following are the detailed steps of this process:

[0051] Selecting a suitable robotic arm model for handling the target material is the first step in the process. This requires a comprehensive analysis based on the target material's identification data: Analyzing the target material's attributes, including information such as the material's size, shape, weight, and gripping points, to determine how the material will be gripped. The specific device in which the material is located and its location within the warehouse are factors to consider when selecting a robotic arm. The status of all current robotic arms, including their position and operational status, is examined to select the robotic arm model that is closest to the target device and has the appropriate gripping capabilities. The selection of a robotic arm also considers compatibility with existing production lines, warehouse layout, and other automated equipment, as well as whether it can meet the speed and accuracy requirements for material handling.

[0052] Once the target robot model is determined, the next step is to plan the optimal path for the robot to ensure the rapid and safe transfer of materials from the warehouse to the target slot on the production line: clarify the starting position of the robot and the location of the device containing the target material, as well as the specific location of the target slot on the production line. Path planning needs to consider the distribution of obstacles in the warehouse and on the production line, as well as how to utilize factors such as the maximum travel range and minimum turning radius of the robot to achieve the shortest path and the highest efficiency. When planning the path, built-in safety mechanisms are also required to ensure that the robot does not collide with people or equipment during movement, and how to quickly adjust the path or suspend operations in the event of an emergency.

[0053] Finally, based on the robot's path data, the target slot matching mode is determined. This involves arranging the robot's operations to precisely place the target material in the target slot. Based on production requirements and material properties, the optimal slot for the material is determined, along with the priority and order of material placement in multi-material tasks. A series of operational instructions are generated, including the robot's grasping, path following, placement, and possible fine-tuning actions such as rotation and tilting, to ensure that the material is accurately placed in the target slot. The matching mode should also include a real-time feedback mechanism to immediately detect and correct any deviations in the robot's operation, ensuring the successful completion of the matching task.

[0054] Through precise analysis of the target material identification data, the most suitable robotic arm model can be intelligently selected, and the optimal path can be planned, ultimately achieving the target slot allocation pattern. This process greatly simplifies the complexity of logistics operations and reduces manual intervention, thereby reducing error rates and improving production efficiency and safety. This automated allocation method has become a key means of improving logistics management efficiency, especially in modern manufacturing that handles large quantities of diverse materials. Throughout the entire process, material identification data serves as the core link, connecting multiple links such as material information, robotic arm selection, path planning, and slot allocation, ensuring the coordination and efficient execution of each step.

[0055] Step S60: Based on the target slot configuration mode, a control instruction set is generated, where the control instruction set is used to control the robot arm execution end to place the target material into the target slot.

[0056] In step S60, precise control of the robotic arm is crucial for efficient material handling and racking. Based on the previously determined target slot racking pattern, a control instruction set is generated and the robotic arm is executed to place the target material, ensuring that all operational details are accurately recorded for future analysis and optimization. The following is a detailed description of this process:

[0057] First, a deep understanding of the target slot configuration model is required, which includes the precise location where the material needs to be placed, the starting and ending points of the robot arm, the gripping method, and any specific material handling requirements. Based on the target slot configuration model, a series of operating instructions will be generated. These instructions are arranged in sequence to form a detailed guide for controlling the work of the robot arm's execution end. The operation sequence may include but is not limited to: initializing the robot arm to the specified starting position; adjusting the gripper at the end of the robot arm according to the target material gripping method; instructing the robot arm to move to the vicinity of the device containing the target material; performing precise gripping actions to ensure that the material is safely removed from its original position; controlling the robot arm to move smoothly to the top of the target slot according to the planned path and posture; adjusting the posture of the end of the robot arm for precise placement according to the size and plane coordinates of the target slot; after placement, confirming that the material is stable to prevent accidental slipping or displacement.

[0058] After generating a set of control instructions, a safety check is performed to ensure that the instructions do not contain any potentially risky actions, such as potential conflicts with other equipment or personnel on the production line. Once the safety-verified control instruction set has been sent to the corresponding control robot arm, the robot arm will execute the instructions until all instructions have been fully executed.

[0059] After the robot completes material placement, it updates the slot placement status database to record the latest status. This involves reading feedback from the robot's execution end to confirm successful material placement in the target slot and obtaining all relevant parameters from the placement process (such as timestamp, robot model, and operator ID). The target material's identification data, slot number, placement time, and placement status information (such as successful placement and any anomalies) are stored in the slot placement status database. The database is then updated with the current occupancy status of the target slot, ensuring the real-time accuracy of the database information. This long-term maintenance of the slot placement status database provides a wealth of historical data for logistics management and equipment scheduling. This data can be used to analyze material flow trends, slot utilization efficiency, and robot performance, providing data support for the continuous improvement and optimization of logistics operations. Through this series of steps, control instructions are generated and executed based on the target slot configuration pattern, ensuring accurate material placement within the production process. Furthermore, maintaining the slot placement status database enables comprehensive monitoring and data accumulation of material flow and robot operation.

[0060] Based on the above steps S10 to S60, in an embodiment of the present invention, production task data is obtained in response to production scheduling instructions, and target material identification data is determined based on the production task data. The target slot matching mode is determined based on the target material identification data, and the target slot matching mode is used to place the target material in the target slot. Based on the target slot matching mode, a control instruction set is generated, and the control instruction set is used to control the robot arm execution end to place the target material in the corresponding target slot. By adopting an automated and data-driven logistics picking process, it is achieved that logistics efficiency can be significantly improved and costs can be reduced, while ensuring the continuity and high-efficiency operation of the production line, thereby solving the technical problem of low overall efficiency of the existing logistics picking process.

[0061] The non-fixed slot racking method for equipment in an embodiment of the present invention determines target material identification data based on production task data, including: determining target material list data based on the production task data; determining target material identification data based on the target material list data based on the material basic data; wherein the material basic data includes at least: part type data, equipment type data, and equipment-part relationship data, wherein the part type data includes at least: recycled standardized containers, global logistics type containers, and special logistics type containers, the equipment type data includes at least: standard equipment and non-standard equipment, and the equipment-part relationship data includes at least: equipment-part correspondence and carrying capacity information. The method of determining target material identification data based on production task data, through refined management and intelligent operation, not only greatly improves the efficiency and accuracy of material management, but also significantly reduces production costs, enhances the controllability of the production process, and enhances the reliability of product quality.

[0062] The non-fixed slot racking method of an embodiment of the present invention is based on material basic data and determines target material identification data according to target bill of materials data, including: determining target storage type data, material usage frequency data and target instrument type data based on material basic data and target bill of materials data; determining target optimal slot data based on target storage type data, material usage frequency data and target instrument type data; determining target racking data based on target optimal slot data, wherein the target racking data includes at least: racking order number data, production process data, instrument order number and bill of materials data; determining corresponding target material identification data according to target racking data based on logistics template data. The method of determining target material identification data based on material basic data not only effectively reduces logistics costs, but also significantly improves production efficiency and management sophistication through intelligent material storage optimization, dynamic racking and detailed distribution guidance.

[0063] Furthermore, based on the target material identification data, the target slot configuration is determined. This includes: determining the target robotic arm model based on the target material identification data; determining the robotic arm path data based on the target robotic arm model; and determining the target slot configuration based on the robotic arm path data. Intelligent analysis of the target material identification data enables rapid matching of the most suitable robotic arm model, ensuring high-speed and high-precision material handling. Accurate robotic arm path planning reduces unnecessary movement distance and time, significantly improving logistics efficiency.

[0064] In one exemplary embodiment, determining the target robotic arm model based on target material identification data includes: determining the target tool position and target material handling method based on the target material identification data; and determining the target robotic arm model based on the target tool position and target material handling method based on the currently idle robotic arm position data. This strategy of determining the target robotic arm model based on target material identification data enables intelligent and precise material handling, significantly improving production efficiency and quality while also enhancing the flexibility and responsiveness of the production line.

[0065] In this embodiment, after generating a control instruction set based on the target slot configuration pattern, the system further includes storing the current target slot storage status in a slot placement status history database. This storage of the current target slot storage status in the slot placement status history database not only enhances the real-time and accuracy of material management but also provides a solid foundation for data analysis, decision support, and safety inventory management, further improving supply chain efficiency, reducing operating costs, and ensuring production continuity.

[0066] Figure 2 Another method for arranging a non-fixed slot for an appliance according to one embodiment of the present invention is as follows: Figure 2 As shown, the method includes the following steps:

[0067] Step S201, obtaining production task data for producing automobile parts;

[0068] Step S202, determining target bill of materials data based on the production task data;

[0069] Step S203, determining target storage type data, material usage frequency data, and target appliance type data based on the material basic data and the target material list data;

[0070] Step S204: determining target material storage requirement data and carrying requirement data based on the target storage type data and the material usage frequency data;

[0071] Step S205 , determining the target optimal slot data based on the slot placement status history database, the target material storage requirement data, the load requirement data, and the target tool type data;

[0072] Step S206, determining target rack data based on the target optimal slot data;

[0073] Step S207, based on the logistics template data and the target rack data, determining the corresponding target material identification data;

[0074] Step S208, determining the target tool position and the target material grabbing method based on the target material identification data;

[0075] Step S209, based on the current idle robot arm position data, the target tool position and the target material grasping method, determining the target robot arm model;

[0076] Step S210, determining the robot arm path data based on the target robot arm model;

[0077] Step S211, determining a target slot configuration mode based on the robot arm path data;

[0078] Step S212: Generate a control instruction set based on the target slot configuration mode.

[0079] Step S213: storing the current storage status of the target slot into a slot placement status history database.

[0080] Based on the above steps S201 to S213, in an embodiment of the present invention, production task data is obtained in response to production scheduling instructions, and target material identification data is determined based on the production task data. The target slot matching mode is determined based on the target material identification data, and the target slot matching mode is used to place the target material in the target slot. Based on the target slot matching mode, a control instruction set is generated, and the control instruction set is used to control the robot arm execution end to place the target material in the corresponding target slot. By adopting an automated and data-driven logistics picking process, the logistics efficiency can be significantly improved and the cost can be reduced. At the same time, the continuity and high-efficiency operation of the production line are guaranteed, thereby solving the technical problem of low overall efficiency of the existing logistics picking process.

[0081] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which 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 network device, etc.) to execute the methods described in each embodiment of the present invention.

[0082] The present invention also provides a device for arranging non-fixed slots for appliances, which is used to implement the above-mentioned embodiments and preferred embodiments. Details already described will not be repeated here. 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.

[0083] Figure 3 This is a structural block diagram of a non-fixed slot arrangement device for an appliance according to one embodiment of the present invention. Figure 3 As shown, the device includes:

[0084] An acquisition module 301 is used to acquire production task data for producing automobile parts, wherein the production task data includes: production plan data, assembly plan data and material serial number information;

[0085] An identification module 302 is configured to determine target material identification data based on the production task data;

[0086] The racking module 303 is used to determine a target slot racking mode based on the target material identification data, wherein the target slot racking mode is used to place the target material in the target slot;

[0087] The control module 304 is used to generate a control instruction set based on the target slot racking mode, and the control instruction set is used to control the robot arm execution end to place the target material into the target slot.

[0088] It should be noted that the above modules can be implemented through software or hardware. For the latter, it can be implemented in the following ways, but not limited to: the above modules are all located in the same processor; or the above modules are located in different processors in any combination.

[0089] According to one embodiment of the present invention, an electronic device is provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the above-mentioned non-fixed slot configuration method for an appliance is executed when the program is running.

[0090] Optionally, in this embodiment, the processor may be configured to execute the following steps through a computer program:

[0091] Step S1, obtaining production task data for producing automobile parts, wherein the production task data includes: production plan data, assembly plan data and material serial number information;

[0092] Step S2, determining target material identification data based on the production task data;

[0093] Step S3, determining a target slot allocation mode based on the target material identification data, wherein the target slot allocation mode is used to place the target material into the target slot;

[0094] Step S4: Based on the target slot configuration mode, a control instruction set is generated, where the control instruction set is used to control the robot arm execution end to place the target material into the target slot.

[0095] According to one embodiment of the present invention, a computer-readable storage medium is also provided, which includes a stored executable program, wherein when the executable program is running, the device where the storage medium is located is controlled to execute the above-mentioned non-fixed slot configuration method for the device.

[0096] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0097] Step S1, obtaining production task data for producing automobile parts, wherein the production task data includes: production plan data, assembly plan data and material serial number information;

[0098] Step S2, determining target material identification data based on the production task data;

[0099] Step S3, determining a target slot allocation mode based on the target material identification data, wherein the target slot allocation mode is used to place the target material into the target slot;

[0100] Step S4: Based on the target slot configuration mode, a control instruction set is generated, where the control instruction set is used to control the robot arm execution end to place the target material into the target slot.

[0101] Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

[0102] According to one embodiment of the present invention, a computer program product is also provided, including a computer program, which implements the above-mentioned method for non-fixed slot configuration of appliances when executed by a processor.

[0103] Optionally, in this embodiment, the computer program product may be configured as a computer program for executing the following steps:

[0104] Step S1, obtaining production task data for producing automobile parts, wherein the production task data includes: production plan data, assembly plan data and material serial number information;

[0105] Step S2, determining target material identification data based on the production task data;

[0106] Step S3, determining a target slot allocation mode based on the target material identification data, wherein the target slot allocation mode is used to place the target material into the target slot;

[0107] Step S4: Based on the target slot configuration mode, a control instruction set is generated, where the control instruction set is used to control the robot arm execution end to place the target material into the target slot.

[0108] 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.

[0109] 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.

[0110] In the several 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 the 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.

[0111] The units described as separate components may or may not be physically separate, and 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 may be selected according to actual needs to achieve the purpose of the present embodiment.

[0112] 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.

[0113] 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 network device, etc.) to perform all or part of the steps of the method described in 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 codes.

[0114] The above is only a preferred embodiment 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 within the scope of protection of the present invention.

Claims

1. A method for arranging equipment in non-fixed slots, characterized in that: include: Acquire production task data for producing automobile parts, wherein the production task data includes: production plan data, assembly plan data and material serial number information; Determining target material identification data based on the production task data; Determine a target slot allocation mode based on the target material identification data, wherein the target slot allocation mode is used to place the target material into the target slot; Based on the target slot racking mode, a control instruction set is generated, and the control instruction set is used to control the robot arm execution end to place the target material into the target slot.

2. The method for arranging non-fixed slots of an appliance according to claim 1, characterized in that: Determining the target material identification data based on the production task data includes: Determining target bill of materials data based on the production task data; Based on the material basic data and according to the target material list data, determining the target material identification data; Among them, the material basic data at least includes: part type data, instrument type data and instrument-part relationship data, wherein the part type data at least includes: recyclable standardized containers, global logistics type containers and special logistics type containers, the instrument type data at least includes: standard instruments and non-standard instruments, and the instrument-part relationship data at least includes: the correspondence between instruments and parts and carrying capacity information.

3. The method for arranging non-fixed slots of an appliance according to claim 2, characterized in that: Based on the material basic data and according to the target material list data, the target material identification data is determined, including: Determining target storage type data, material usage frequency data, and target appliance type data based on the material base data and the target material list data; Determining target optimal slot data based on the target storage type data, the material usage frequency data, and the target appliance type data; Determine target racking data based on the target optimal slot data, wherein the target racking data at least includes: racking order number data, production process data, equipment order number and bill of materials data; Based on the logistics template data and according to the target rack data, the corresponding target material identification data is determined.

4. The method for arranging non-fixed slots of an appliance according to claim 3, characterized in that: Determining the target optimal slot data based on the target storage type data, the material usage frequency data, and the target appliance type data includes: Determining target material storage requirement data and carrying requirement data based on the target storage type data and the material usage frequency data, wherein the target material storage requirement data at least includes: storage temperature data, storage humidity data, storage shockproof level, and storage antistatic level; The target optimal slot data is determined based on a slot placement status history database, the target material storage requirement data, the load requirement data, and the target tool type data.

5. The method for arranging non-fixed slots of an appliance according to claim 1, characterized in that: Determining the target slot configuration mode based on the target material identification data includes: Determining a target robotic arm model based on the target material identification data; Determining the path data of the robotic arm based on the target robotic arm model; Based on the robot arm path data, a target slot configuration mode is determined.

6. The method for arranging non-fixed slots of an appliance according to claim 5, characterized in that: Determining the target robotic arm model based on the target material identification data includes: Determining a target tool position and a target material grabbing method based on the target material identification data; Based on the current idle robot arm position data, the target robot arm model is determined according to the target tool position and the target material grasping method.

7. The method for arranging non-fixed slots of an appliance according to claim 1, characterized in that: After generating the control instruction set based on the target slot configuration mode, the method further includes: The current storage status of the target slot is stored in a slot placement status history database.

8. A non-fixed slot mounting device for an appliance, characterized in that: include: An acquisition module, configured to acquire production task data for producing automobile parts, wherein the production task data includes: production plan data, assembly plan data, and material serial number information; an identification module, configured to determine target material identification data based on the production task data; a racking module, configured to determine a target slot racking mode based on the target material identification data, wherein the target slot racking mode is used to place the target material in the target slot; The control module is used to generate a control instruction set based on the target slot racking mode, and the control instruction set is used to control the robot arm execution end to place the target material into the target slot.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored executable program, wherein when the executable program is run, the device where the storage medium is located is controlled to execute the non-fixed slot configuration method for an appliance according to any one of claims 1 to 7.

10. A computer program product, characterized in that It comprises a computer program which, when executed by a processor, implements the method for non-fixed slot configuration of an appliance according to any one of claims 1 to 7.

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