Warehouse goods packaging material management method based on Internet of Things
Through IoT technology, optimized the material management of warehousing cargo packaging, combined with path planning and equipment collaborative operations, the problem of insufficient coordination between path planning and equipment scheduling in the existing technology is solved, and efficient and stable material handling and quality control is achieved.
Patent Information
- Application Number
- CN202510690587.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-27
- Publication Date
- 2025-08-15
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
In the prior art, warehousing and transportation path optimization and equipment scheduling are insufficient, and the Internet of Things perception capability is lacking, resulting in low handling efficiency and difficult to guarantee the quality of packaging materials.
The Internet of Things-based warehousing goods packaging material management method is adopted, and the comprehensive path planning model and multi-equipment collaborative operation optimization model are used, and the path is dynamically adjusted in combination with the equipment operation status, and the material status is monitored in real time and quality control is carried out to optimize task allocation and equipment collaborative operation.
It improves handling efficiency, reduces equipment no-load rate, ensures the high-quality state of packaging materials, reduces transportation losses, and improves handling stability and quality control capabilities.
Smart Images
Figure CN120494239A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of material management, and in particular to a method for managing packaging materials of stored goods based on the Internet of Things. Background Art
[0002] In modern warehouse management, the efficient flow of packaging materials is crucial to the stable operation of the supply chain. With the development of Internet of Things technology, the management of warehouse goods has gradually evolved from traditional manual scheduling to intelligent and automated directions.
[0003] In the existing technology, there are deficiencies in the coordination between warehouse and transportation route optimization and equipment scheduling: the existing route planning and equipment scheduling strategies lack a collaborative optimization mechanism, route planning fails to fully integrate the equipment operating status, and equipment scheduling fails to dynamically adapt to the route optimization results, resulting in a decrease in overall handling efficiency.
[0004] Existing technologies lack the ability to monitor and dynamically adjust the real-time quality of packaging materials: there is a lack of IoT sensing capabilities to monitor the impact force, vibration intensity, pressure, etc. during material handling in real time, and a closed-loop quality control system has not been formed. This may result in packaging materials being damaged during transportation, affecting the final delivery quality. Summary of the Invention
[0005] In view of the deficiencies of the existing technology, the present invention provides a warehouse cargo packaging material management method based on the Internet of Things to solve the problems raised in the above background technology.
[0006] To achieve the above object, the present invention provides the following technical solutions: In a first aspect, an embodiment of the present invention provides a method for managing packaging materials for warehoused goods based on the Internet of Things, comprising the following steps: S1. Collect the real-time status of packaging materials to manage packaging material inventory and obtain inventory data; S2. Perform material scheduling based on inventory data to obtain scheduling data; S3. Plan the transportation route of the packaging materials according to the scheduling data to obtain route planning data; S4. Perform collaborative operation of the handling equipment according to the path planning data to obtain handling data; S5. Monitor the packaging materials in real time based on the handling data to obtain monitoring data; S6. Perform packaging material quality control based on monitoring data to obtain quality control data; S7. Conduct packaging material cost analysis based on quality control data.
[0007] To further optimize this technical solution, the material scheduling in S2 includes: Based on inventory data, through data analysis methods, the demand for packaging materials within a time period is analyzed, and scheduling is performed based on the real-time inventory quantity. When the inventory quantity of the scheduled packaging materials is less than the threshold, the management personnel are reminded to replenish the inventory in time.
[0008] To further optimize this technical solution, the transportation route planning of the packaging materials in S3 includes: Based on the scheduling data, a comprehensive path planning model is used, combining material attributes and warehouse equipment status to dynamically adjust the optimal path, reduce material handling time, and ensure maximum transportation efficiency.
[0009] To further optimize this technical solution, the comprehensive path planning model includes: Set constraints, construct an objective function to minimize transportation costs, and derive the optimal path based on the results; Model construction: ; in: : minimum path passing cost; : the set of all paths, Representation node To Node Path; :path length; : By path the time required; :equipment speed; :Packaging materials weight; :equipment Maximum load weight; :Packaging materials volume; : The maximum volume of the device; : The collection of all devices; :equipment energy consumption; :equipment The average power consumption.
[0010] To further optimize this technical solution, the constraints include: Path selection constraints: ; Each device Choose at most one path during transportation , cannot be transported on multiple paths at the same time, that is, the path selection variable The maximum value is 1; Equipment carrying capacity constraints: ; For each path , packaging materials Weight Must be less than or equal to the device Maximum load capacity , otherwise the path cannot be selected; Equipment volume constraints: ; Packaging materials Volume Must be less than or equal to the device Maximum volume , otherwise the path Cannot be selected; Device speed constraints: ; The speed of the device Must be less than or equal to the device Maximum permissible speed , otherwise the equipment will not operate or exceed the design parameters; Equipment energy consumption constraints: ; equipment Total energy consumption during transportation Must be less than or equal to the device Maximum energy supply , otherwise the equipment cannot complete the transportation task; Path passing time constraint: ; Transportation route Corresponding time Must be less than or equal to the device Maximum acceptable shipping time , that is, the transportation task is completed within the limited time.
[0011] To further optimize this technical solution, the collaborative operation of the handling equipment in S4 includes: Based on the path planning data, multiple devices in the warehouse are scheduled to work together. By using the multi-device collaborative operation optimization model, it is ensured that multiple devices can complete the handling tasks efficiently.
[0012] To further optimize this technical solution, the multi-device collaborative operation optimization model includes: ; in: : Decision variable, representing the device Whether assigned to carry materials , if it is 1, it is responsible for transportation, and if it is 0, it is not responsible for transportation; :equipment Current task load quantity; :equipment Maximum number of mission loads; : Indicates the current busyness of the device, the larger the value, the busier it is; : Energy consumption adjustment parameters.
[0013] To further optimize this technical solution, the real-time monitoring of packaging materials in S5 includes: The equipment handling data is transmitted to the central monitoring platform in real time through the Internet of Things, allowing warehouse managers to remotely monitor the real-time status of material handling, detect abnormal situations and adjust work arrangements in a timely manner.
[0014] To further optimize this technical solution, the packaging material quality control in S6 includes: Based on the monitoring data, the quality control model is used to calculate the predicted value of the damage degree of the packaging material. When the predicted value of the damage degree exceeds the set threshold, the parameters of the equipment are adjusted while meeting the constraints.
[0015] To further optimize this technical solution, the packaging material cost analysis in S7 includes: Based on quality control data, big data analysis technology is used to analyze the procurement cost, usage frequency, and loss rate of various packaging materials to achieve comprehensive cost control of packaging materials.
[0016] In a second aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of a warehouse cargo packaging material management method based on the Internet of Things as described in the first aspect of the present invention are implemented.
[0017] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of a warehouse cargo packaging material management method based on the Internet of Things as described in the first aspect of the present invention are implemented.
[0018] Compared with the existing technology, the present invention provides a warehouse cargo packaging material management method based on the Internet of Things, which has the following beneficial effects: This IoT-based warehouse cargo packaging material management method forms a path-equipment collaborative optimization mechanism through a comprehensive path planning model and a multi-equipment collaborative operation optimization model, ensuring the shortest path planning and matching with equipment capabilities, optimizing task allocation, reducing equipment idle rate, and improving overall handling efficiency.
[0019] By introducing IoT sensors into the quality control model to monitor key parameters such as impact force, acceleration, and vibration intensity, the degree of damage to the material packaging can be calculated. When the damage risk is detected to exceed the set threshold, adjustments are made to the equipment speed, acceleration, and packaging material stacking method to ensure that the packaging materials maintain high quality throughout the entire storage and handling process, thereby improving the quality of the packaging materials, reducing transportation losses, and improving the stability of packaging material handling. BRIEF DESCRIPTION OF THE DRAWINGS
[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0021] Figure 1 This is a flow chart of a warehouse cargo packaging material management method based on the Internet of Things proposed by the present invention; Figure 2 This is a flow chart of a comprehensive path planning model for a warehouse cargo packaging material management method based on the Internet of Things proposed by the present invention; Figure 3 This is a flow chart of a multi-device collaborative operation optimization model for a warehouse cargo packaging material management method based on the Internet of Things proposed by the present invention; Figure 4 This is a flow chart of a quality control model for a warehouse cargo packaging material management method based on the Internet of Things proposed by the present invention. DETAILED DESCRIPTION
[0022] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.
[0023] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.
[0024] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it constitute a separate or selective embodiment that is mutually exclusive with other embodiments.
[0025] Example 1: Reference Figures 1 to 4 , which is the first embodiment of the present invention, provides a method for managing storage cargo packaging materials based on the Internet of Things, comprising the following steps: S1. Collect the real-time status of packaging materials to manage packaging material inventory and obtain inventory data.
[0026] In this embodiment, packaging material inventory management includes: By using IoT devices, a comprehensive perception network is established in the storage facilities to monitor the status of packaging materials in real time, realize dynamic tracking of packaging materials and update inventory information.
[0027] S2. Perform material scheduling based on inventory data to obtain scheduling data.
[0028] In this embodiment, material scheduling includes: Based on inventory data, using data analysis methods (existing technology), the demand for packaging materials within a time period (e.g., 12 hours) is analyzed, and scheduling is performed based on the real-time inventory quantity. When the inventory quantity of the scheduled packaging materials is less than a threshold (e.g., 10% of the upper limit of the inventory quantity of this type of packaging materials), the management personnel are reminded to replenish the inventory in a timely manner.
[0029] S3. Plan the transportation route of the packaging materials according to the scheduling data to obtain route planning data.
[0030] In this embodiment, the transportation route planning of packaging materials includes: Based on the scheduling data, a comprehensive path planning model is used, combining material attributes and warehouse equipment status to dynamically adjust the optimal path, reduce material handling time, and ensure maximum transportation efficiency.
[0031] Furthermore, the comprehensive path planning model includes: Set constraints, construct an objective function to minimize transportation costs, and derive the optimal path based on the results; Model construction: ; in: : minimum path passing cost; : the set of all paths, Representation node To Node Path; :path length; : By path the time required; :equipment speed; :Packaging materials weight; :equipment Maximum load weight; :Packaging materials volume; : The maximum volume of the device; : The collection of all devices; :equipment energy consumption; :equipment The average power consumption.
[0032] Model usage: Path selection: Based on the material scheduling data obtained in step S2, all paths are calculated to obtain information such as the transportation time and energy consumption of each path. The path cost is comprehensively calculated, and the path with the lowest cost is selected. The resulting path planning data will be used in step S4; Dynamic adjustment: When the device status changes, the model dynamically adjusts the path and selects the path with the lowest cost; Multi-objective balance: By optimizing the balance of different objectives in the model, including transportation time and energy consumption, path planning not only considers time cost, but also energy consumption and equipment load, ensuring the efficiency and economy of the transportation process.
[0033] Furthermore, the constraints include: Path selection constraints: ; Each device Choose at most one path during transportation , cannot be transported on multiple paths at the same time, that is, the path selection variable The maximum value is 1; Equipment carrying capacity constraints: ; For each path , packaging materials Weight Must be less than or equal to the device Maximum load capacity , otherwise the path cannot be selected; Equipment volume constraints: ; Packaging materials Volume Must be less than or equal to the device Maximum volume , otherwise the path Cannot be selected; Device speed constraints: ; The speed of the device Must be less than or equal to the device Maximum permissible speed , otherwise the equipment will not operate or exceed the design parameters; Equipment energy consumption constraints: ; equipment Total energy consumption during transportation Must be less than or equal to the device Maximum energy supply , otherwise the equipment cannot complete the transportation task; Path passing time constraint: ; Transportation route Corresponding time Must be less than or equal to the device Maximum acceptable shipping time , that is, the transportation task is completed within the limited time.
[0034] S4. Perform collaborative operation of the transport equipment according to the path planning data to obtain transport data.
[0035] In this embodiment, the coordinated operation of the transport equipment includes: Based on the path planning data, multiple devices in the warehouse are scheduled to work together. By using the multi-device collaborative operation optimization model, it is ensured that multiple devices can complete the handling tasks efficiently, avoiding conflicts and idle time between devices, improving the efficiency of material handling in the warehouse, and achieving the optimal allocation of equipment resources.
[0036] Furthermore, the multi-device collaborative operation optimization model includes: ; in: : Decision variable, representing the device Whether assigned to move materials , if it is 1, it is responsible for transportation, and if it is 0, it is not responsible for transportation; :equipment Current task load quantity; :equipment Maximum number of mission loads; : Indicates the current busyness of the device, the larger the value, the busier it is; : Energy consumption adjustment parameters.
[0037] Model usage: Path planning input: Obtain the path planning data from step S3 and determine the tasks that the device needs to perform based on the path planning data; Device status initialization: confirm the current load, remaining storage volume, and battery power of all devices; Task allocation calculation: Calculate the comprehensive cost of each device performing the task, and set the value of the decision variable based on the cost to decide whether to assign the task to the device; Device scheduling: When the task load of a device exceeds its maximum task load, the task is reallocated to other devices. When the energy consumption of a device is greater than the remaining energy of the device, the task is reallocated to other devices, and charging station nodes are added during the path planning stage. Collaborative work execution: Each device performs collaborative work according to the assigned tasks, and the equipment's handling data is used for real-time monitoring and analysis in S5.
[0038] S5. Perform real-time monitoring of packaging materials based on the handling data to obtain monitoring data.
[0039] In this embodiment, real-time monitoring of packaging materials includes: Equipment handling data, including the operating status of each device and the progress of material transportation, is transmitted to the central monitoring platform in real time through the Internet of Things, allowing warehouse managers to remotely monitor the real-time status of material handling, detect abnormal situations and adjust work arrangements in a timely manner, ensuring the efficiency and safety of every link in material scheduling.
[0040] S6. Perform packaging material quality control based on the monitoring data to obtain quality control data.
[0041] In this embodiment, packaging material quality control includes: Based on the monitoring data, including the impact pressure, acceleration, speed, and compression force during the material handling process, the quality control model is used to calculate the predicted value of the damage degree of the packaging materials. When the predicted value of the damage degree exceeds the set threshold, the equipment parameters are adjusted while meeting the constraints. This includes adjusting the equipment speed, controlling the equipment acceleration, adjusting the stacking method of the packaging materials, and redistributing the packaging materials, thereby ensuring the quality of the packaging materials, reducing the damage rate during transportation, and improving the stability of the transportation process.
[0042] Furthermore, the quality control model includes: ; in: :Packaging materials The predicted value of the packaging damage degree, the smaller the value, the less packaging damage; : The total number of stages that packaging materials go through during transportation, including starting, acceleration, centering movement, and deceleration; : No. The magnitude of the impact force during each stage, including the instantaneous impact force caused by equipment acceleration and emergency stop; : The maximum impact force that the packaging material can withstand; :The equipment is in The magnitude of the acceleration in each stage affects the intensity of the impact force; : The maximum acceleration that the packaging material can withstand affects the stability of the equipment during handling; :The equipment is in The speed of each stage affects the vibration intensity during equipment transportation; : The maximum safe transportation speed that the packaging material can withstand; :Packaging materials the amount of pressure experienced; : The maximum compressive strength of the packaging material.
[0043] Model usage: Data acquisition: The optimal path and handling equipment information are acquired through steps S3 and S4. Data acquisition is performed through step S5 to acquire data including impact force, acceleration, speed, and pressure during the handling process, which are used to calculate the predicted value of the damage degree of the packaging material. Damage Degree Calculation: Data is input into the model to calculate the predicted damage degree of the packaging material. When the value is greater than 1, it indicates that the packaging material is highly damaged under the handling conditions and is easily damaged. When the value is much less than 1, it indicates that the packaging material is extremely damaged under the handling conditions and is not easily damaged. When the damage degree exceeds the threshold, adjustment measures are taken. Implement adjustment measures: Use methods including adjusting equipment speed, optimizing equipment acceleration, redistributing materials, and adjusting stacking methods to reduce the degree of damage to packaging materials.
[0044] S7. Conduct packaging material cost analysis based on quality control data.
[0045] In this embodiment, the packaging material cost analysis includes: Based on quality control data, through big data analysis technology (existing technology), we analyze the procurement cost, usage frequency, and loss rate of various packaging materials, helping companies better control the cost expenditure of packaging materials and achieve comprehensive cost control of packaging materials, from procurement, use to loss, providing detailed data support for cost control.
[0046] Example 2: This embodiment also provides a computer device, which is applicable to a method for managing packaging materials of warehouse goods based on the Internet of Things, and includes a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement a method for managing packaging materials of warehouse goods based on the Internet of Things as proposed in the above embodiment.
[0047] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, it implements a warehouse cargo packaging material management method based on the Internet of Things as proposed in the above embodiment.
[0048] The computer device may be a terminal, comprising a processor, memory, a communication interface, a display, and an input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and computer programs. The internal memory provides an environment for the operating system and computer programs stored in the non-volatile storage media. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication. Wireless communication may be achieved via Wi-Fi, a carrier network, NFC (near-field communication), or other technologies. The display of the computer device may be a liquid crystal display or an electronic ink display. The input device may be a touchscreen overlay on the display, buttons, a trackball, or a touchpad on the computer device housing, or an external keyboard, touchpad, or mouse.
[0049] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or the portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.
[0050] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.
[0051] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting, or processing it in another suitable manner as necessary, and then storing it in a computer memory.
[0052] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.
[0053] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.
Claims
1. A method for managing packaging materials of warehouse goods based on the Internet of Things, characterized in that: The following steps are involved: S1. Collect the real-time status of packaging materials to manage packaging material inventory and obtain inventory data; S2. Perform material scheduling based on inventory data to obtain scheduling data; S3. Plan the transportation route of the packaging materials according to the scheduling data to obtain route planning data; S4. Perform collaborative operation of the handling equipment according to the path planning data to obtain handling data; S5. Monitor the packaging materials in real time based on the handling data to obtain monitoring data; S6. Perform packaging material quality control based on monitoring data to obtain quality control data; S7. Conduct packaging material cost analysis based on quality control data.
2. The method for managing storage cargo packaging materials based on the Internet of Things according to claim 1, characterized in that: The material scheduling in S2 includes: Based on inventory data, through data analysis methods, the demand for packaging materials within a time period is analyzed, and scheduling is performed based on the real-time inventory quantity. When the inventory quantity of the scheduled packaging materials is less than the threshold, the management personnel are reminded to replenish the inventory in time.
3. The method for managing storage cargo packaging materials based on the Internet of Things according to claim 1, characterized in that: The transportation route planning of the packaging materials in S3 includes: Based on the scheduling data, a comprehensive path planning model is used, combining material attributes and warehouse equipment status to dynamically adjust the optimal path, reduce material handling time, and ensure maximum transportation efficiency.
4. The method for managing storage cargo packaging materials based on the Internet of Things according to claim 3, characterized in that: The comprehensive path planning model includes: Set constraints, construct an objective function to minimize transportation costs, and derive the optimal path based on the results; Model construction: ； in: : minimum path passing cost; : the set of all paths, Representation node To Node Path; :path length; : By path the time required; :equipment speed; :Packaging materials weight; :equipment Maximum load weight; :Packaging materials volume; : The maximum volume of the device; : The collection of all devices; :equipment energy consumption; :equipment The average power consumption.
5. The method for managing storage cargo packaging materials based on the Internet of Things according to claim 4, characterized in that: The constraints include: Path selection constraints: ； Each device Choose at most one path during transportation , cannot be transported on multiple paths at the same time, that is, the path selection variable The maximum value is 1; Equipment carrying capacity constraints: ； For each path , packaging materials Weight Must be less than or equal to the device Maximum load capacity , otherwise the path cannot be selected; Equipment volume constraints: ； Packaging materials Volume Must be less than or equal to the device Maximum volume , otherwise the path Cannot be selected; Device speed constraints: ； The speed of the device Must be less than or equal to the device Maximum permissible speed , otherwise the equipment will not operate or exceed the design parameters; Equipment energy consumption constraints: ； equipment Total energy consumption during transportation Must be less than or equal to the device Maximum energy supply , otherwise the equipment cannot complete the transportation task; Path passing time constraint: ； Transportation route Corresponding time Must be less than or equal to the device Maximum acceptable shipping time , that is, the transportation task is completed within the limited time.
6. The method for managing storage cargo packaging materials based on the Internet of Things according to claim 1, characterized in that: The collaborative operation of the handling equipment in S4 includes: Based on the path planning data, multiple devices in the warehouse are scheduled to work together. By using the multi-device collaborative operation optimization model, it is ensured that multiple devices can complete the handling tasks efficiently.
7. The method for managing storage cargo packaging materials based on the Internet of Things according to claim 6, characterized in that: The multi-device collaborative operation optimization model includes: ； in: : Decision variable, representing the device Whether assigned to move materials , if it is 1, it is responsible for transportation, and if it is 0, it is not responsible for transportation; :equipment Current task load quantity; :equipment Maximum number of mission loads; : Indicates the current busyness of the device, the larger the value, the busier it is; : Energy consumption adjustment parameters.
8. The method for managing storage cargo packaging materials based on the Internet of Things according to claim 1, characterized in that: The real-time monitoring of packaging materials in S5 includes: The equipment handling data is transmitted to the central monitoring platform in real time through the Internet of Things, allowing warehouse managers to remotely monitor the real-time status of material handling, detect abnormal situations and adjust work arrangements in a timely manner.
9. The method for managing storage cargo packaging materials based on the Internet of Things according to claim 1, characterized in that: The packaging material quality control in S6 includes: Based on the monitoring data, the quality control model is used to calculate the predicted value of the damage degree of the packaging material. When the predicted value of the damage degree exceeds the set threshold, the parameters of the equipment are adjusted while meeting the constraints.
10. The method for managing storage cargo packaging materials based on the Internet of Things according to claim 1, characterized in that: The packaging material cost analysis in S7 includes: Based on quality control data, big data analysis technology is used to analyze the procurement cost, usage frequency, and loss rate of various packaging materials to achieve comprehensive cost control of packaging materials.