Zero cigarette warehouse management system

Abstract

The invention discloses a zero cigarette warehouse management system which comprises a data docking module which is bidirectionally docked with a warehouse management system based on a dual-protocol communication mechanism, an intelligent goods lattice module which is used for zero cigarette storage and intelligent detection and display, and an intelligent scheduling module which generates a dynamic sorting path according to the real-time state of goods lattices based on a three-dimensional path planning algorithm. The intelligent checking module carries out intelligent guiding checking based on a mixed checking process; through real-time interaction with a warehouse management system, a manual input link is eliminated, the information transmission delay and error rate are reduced, through lamplight projection, dynamic lamplight and display screen cooperative indication work, the phenomena of wrong taking and missing taking are reduced, the invalid moving distance is shortened, the human resource utilization rate is optimized, and the sorting efficiency is remarkably improved; real-time accurate verification of the inventory state is realized through pressure sensing, and inventory checking is performed in cooperation with the mixed verification process and the generated inventory state thermodynamic diagram, so that the efficiency of the checking strategy is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of warehousing and logistics management, and in particular to a cigarette storage management system. Background Art

[0002] Traditional zero-cigarette warehouses require manual picking after receiving tasks, which has low picking efficiency. At the same time, there is no prompt and picking and checking relies on human experience, which is very easy to make mistakes. Manual counting is also required during inventory counting, which is time-consuming. The existing system lacks real-time dynamic interaction capabilities and cannot achieve intelligent guidance of the operation process, resulting in "detours" in manual picking and inventory counting routes, affecting operation efficiency. Therefore, the present invention proposes a zero-cigarette warehouse management system to solve the problems existing in the existing technology. Summary of the Invention

[0003] In response to the above problems, the purpose of the present invention is to propose a zero-cigarette warehouse management system, which eliminates the manual input link through real-time interaction with the warehouse management system, reduces information transmission delay and error rate, and uses light projection, dynamic lighting and display screens to coordinate instructions for operations, thereby reducing the phenomenon of wrong or missed items, shortening the invalid movement distance, optimizing human resource utilization, and significantly improving picking efficiency. It uses pressure sensing to achieve real-time and accurate verification of inventory status, and cooperates with the mixed verification process and the generation of inventory status heat maps for inventory counting, effectively improving the efficiency of the inventory counting strategy.

[0004] To achieve the purpose of the present invention, the present invention is implemented through the following technical solutions: a zero-cigarette warehouse management system, including a data docking module, an intelligent cargo grid module, an intelligent scheduling module and an intelligent inventory module. The data docking module is bidirectionally docked with the warehouse management system based on a dual-protocol communication mechanism. The intelligent cargo grid module is used for zero-cigarette storage and intelligent detection and display. The intelligent scheduling module generates a dynamic picking path according to the real-time status of the cargo grid based on a three-dimensional path planning algorithm. The intelligent inventory module performs intelligent guided inventory based on a hybrid verification process.

[0005] Further improvements are: the dual-protocol communication mechanism includes the MQTT real-time data push protocol and the RESTfulAPI timed verification protocol, the data docking module includes a data cleaning module and a message management module, the data cleaning module filters abnormal data based on a sliding window algorithm, and the message management module is used for real-time push and subscription of job instructions.

[0006] A further improvement is that when the data cleaning module filters abnormal data, the actual deviation value Δ satisfies the following formula and is determined to be abnormal data

[0007] Δ=|V 实际 -V 预期 |>μ+3σ

[0008] Where V 实际 Indicates the actual value of the inventory of zero cigarettes, V 预期 represents the theoretical inventory expectation value on the warehouse management system side, μ represents the historical mean, and σ represents the standard deviation;

[0009] The historical mean μ is calculated by the following formula

[0010]

[0011] The standard deviation σ is calculated by the following formula

[0012]

[0013] Where N is the sliding window size, Δ i is the actual deviation value of the i-th operation;

[0014] Further improvements are: the intelligent cargo grid module includes a dynamic display module, an indicator light module and a sensing control module. The dynamic display module is used to display the zero-cigarette brand, real-time inventory, historical in and out records of the cargo grid and operation instructions. The indicator light module responds to system instructions in real time based on a multi-color LED array to switch the lighting status. The sensing control module is used to monitor and control the cargo grid status, which includes a pressure sensor array and a capacitive touch button, which are respectively used to detect the zero-cigarette inventory, eliminate task instructions and identify cargo grid information.

[0015] Further improvements are: the intelligent scheduling module includes a weight calculation module, a task redistribution module and an intelligent guidance module, the weight calculation module generates a dynamic picking path based on a real-time dynamic weight calculation model, the task redistribution module redistributes tasks between operators alternately based on the real-time positions of the operators, and the intelligent guidance module instructs the operators to move and pick according to the dynamically updated planned path based on light projection.

[0016] A further improvement is that the real-time dynamic weight calculation model performs nonlinear fitting on the cargo grid position coordinates (x, y, z) with the equipment load rate L and the environmental interference factor E to generate a path weight value, which is expressed by the following formula:

[0017] W=α·f(x,y,z)+β·L+γ·E

[0018] Among them, α, β, and γ are dynamic adjustment coefficients.

[0019] Further improvements are as follows: the hybrid verification process includes an initial inventory stage, a re-inventory stage and a final inventory stage. The initial inventory stage automatically plans an S-shaped inventory path based on UWB positioning technology. The re-inventory stage detects abnormalities in the stacking of zero-cigarettes in the cargo compartment based on millimeter-wave radar. The final inventory stage generates an inventory status heat map including a confidence score based on the positioning data of the initial inventory stage and the detection data of the re-inventory settlement.

[0020] A further improvement is that the intelligent inventory module includes a periodic strategy generation module and a difference processing module. The periodic strategy generation module generates an inventory strategy for the intelligent cargo grid module based on the daily, weekly and monthly inventory frequencies. The difference processing module is used to automatically generate inventory adjustment instructions and attach an operator's digital signature.

[0021] The beneficial effects of the present invention are as follows: the present invention eliminates the manual input link through real-time interaction with the warehouse management system, reduces information transmission delays and error rates, and coordinates instructions for operations through light projection, dynamic lighting and display screens to reduce the phenomenon of wrong or missed items, shorten the invalid movement distance, optimize human resource utilization, and significantly improve picking efficiency. It realizes real-time and accurate verification of inventory status through pressure sensing, cooperates with the mixed verification process and generates inventory status heat maps for inventory counting, effectively improving the efficiency of the inventory counting strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a system architecture diagram of the present invention. DETAILED DESCRIPTION

[0023] In order to deepen the understanding of the present invention, the present invention will be further described in detail below with reference to the examples. The examples are only used to explain the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0024] according to Figure 1 As shown, this embodiment provides a zero-cigarette warehouse management system, including a data docking module, an intelligent cargo grid module, an intelligent scheduling module and an intelligent inventory module. The data docking module is bidirectionally connected to the warehouse management system based on a dual-protocol communication mechanism. The intelligent cargo grid module is used for zero-cigarette storage and intelligent detection and display. The intelligent scheduling module generates a dynamic picking path according to the real-time status of the cargo grid based on a three-dimensional path planning algorithm. The intelligent inventory module performs intelligent guided inventory based on a hybrid verification process.

[0025] After the warehouse management system completes stocking, the data docking module sends the target cargo grid list to the smart cargo grid module through the differential update mechanism;

[0026] After receiving the instruction, the intelligent cargo grid module distinguishes the orders through the flashing frequency of the multi-color LED array and links the pre-stored reference value of the pressure sensor array;

[0027] After picking is completed, inventory deduction is triggered through the capacitive touch button, and the deviation rate between the pressure sensor array data and the instruction value is automatically compared. If it exceeds the preset value, an alarm reminder will be activated and a review will be carried out, that is, |deviation weight-theoretical difference|>threshold, and an abnormal alarm will be issued.

[0028] The dual-protocol communication mechanism includes the MQTT real-time data push protocol and the RESTfulAPI timed verification protocol. The data docking module includes a data cleaning module and a message management module. The data cleaning module filters abnormal data based on a sliding window algorithm, and the message management module is used for real-time push and subscription of job instructions.

[0029] When the data cleaning module filters abnormal data, the actual deviation value Δ satisfies the following formula and is judged as abnormal data

[0030] Δ=|V 实际 -V 预期 |>μ+3σ

[0031] Where V 实际 Indicates the actual inventory value of zero cigarettes, which is the current actual inventory quantity of the shelf collected by sensors, manual input or system in real time, V 预期 represents the theoretical inventory expectation value on the warehouse management system side, which is the standardized data received from the warehouse management system. μ represents the historical mean, which is calculated based on the sliding window algorithm and reflects the normal operation fluctuation range. σ represents the standard deviation and represents the data fluctuation range.

[0032] The historical mean μ is calculated by the following formula

[0033]

[0034] The standard deviation σ is calculated by the following formula

[0035]

[0036] Where N is the sliding window size, Δ i is the actual deviation value of the i-th operation.

[0037] Update μ and σ based on a sliding window to adapt to business changes (such as peak / off-season fluctuations); the 3σ threshold can filter out 99.7% of normal fluctuations and reduce the false alarm rate.

[0038] The intelligent cargo grid module includes a dynamic display module, an indicator light module and a sensing control module. The dynamic display module is used to display the zero-smoking brand, real-time inventory, historical in and out records of the cargo grid and operation instructions. The indicator light module responds to system instructions in real time based on a multi-color LED array to switch the lighting status. The sensing control module is used to monitor and control the cargo grid status, which includes a pressure sensor array and a capacitive touch button, which are respectively used to detect the zero-smoking inventory, eliminate task instructions and identify cargo grid information.

[0039] The dynamic display module is specifically based on dual-mode display technology. The main display area displays the quantity to be picked in real time in the form of barcodes, and the auxiliary information area scrolls to display the historical in and out of the cargo grid and environmental parameters.

[0040] The multi-color LED array has a three-stage operation guidance function. The red breathing light indicates the cargo box to be picked, the green solid light indicates that the picking is completed and awaiting confirmation, and the blue flashing light indicates the cargo box that needs to be verified during the inventory task.

[0041] The capacitive touch buttons use capacitive multi-touch technology. A single-finger click confirms an operation, a two-finger long press triggers an inventory anomaly report, and a sliding gesture switches the display mode.

[0042] The intelligent scheduling module includes a weight calculation module, a task redistribution module and an intelligent guidance module. The weight calculation module generates a dynamic picking path based on a real-time dynamic weight calculation model. The task redistribution module redistributes tasks between operators based on their real-time positions. The intelligent guidance module instructs operators to move and pick according to the dynamically updated planned path based on light projection.

[0043] The real-time dynamic weight calculation model performs nonlinear fitting on the cargo grid position coordinates (x, y, z) with the equipment load rate L and the environmental interference factor E to generate the path weight value, which is expressed by the following formula:

[0044] W=α·f(x,y,z)+β·L+γ·E

[0045] Among them, α, β, and γ are dynamic adjustment coefficients.

[0046] The hybrid verification process includes the initial inventory stage, the re-inventory stage and the final inventory stage. The initial inventory stage automatically plans an S-shaped inventory route based on UWB positioning technology. The re-inventory stage uses millimeter-wave radar to detect abnormalities in the stacking of zero-cigarettes in the cargo compartment. The final inventory stage generates an inventory status heat map with a confidence score based on the positioning data of the initial inventory stage and the detection data of the re-inventory settlement.

[0047] The intelligent inventory module includes a cycle strategy generation module and a difference processing module. The cycle strategy generation module generates the inventory strategy of the intelligent cargo grid module based on the daily, weekly and monthly inventory frequencies. The difference processing module is used to automatically generate inventory adjustment instructions and attach the operator's digital signature.

[0048] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A cigarette storage management system, characterized by: It includes a data docking module, an intelligent cargo grid module, an intelligent scheduling module and an intelligent inventory module. The data docking module is bidirectionally connected to the warehouse management system based on a dual-protocol communication mechanism. The intelligent cargo grid module is used for zero-cigarette storage and intelligent detection and display. The intelligent scheduling module generates a dynamic picking path according to the real-time status of the cargo grid based on a three-dimensional path planning algorithm. The intelligent inventory module performs intelligent guided inventory based on a hybrid verification process.

2. A cigarette storage management system according to claim 1, characterized in that: The dual-protocol communication mechanism includes the MQTT real-time data push protocol and the RESTful API timed verification protocol. The data docking module includes a data cleaning module and a message management module. The data cleaning module filters abnormal data based on a sliding window algorithm, and the message management module is used for real-time push and subscription of job instructions.

3. The empty cigarette storage management system according to claim 2, characterized in that: When the data cleaning module filters abnormal data, the actual deviation value Δ satisfies the following formula and is determined to be abnormal data. Δ=|V 实际 -V 预期 |>μ+3σ Where V 实际 Indicates the actual value of the inventory of zero cigarettes, V 预期 represents the theoretical inventory expectation value on the warehouse management system side, μ represents the historical mean, and σ represents the standard deviation; The historical mean μ is calculated by the following formula The standard deviation σ is calculated by the following formula Where N is the sliding window size, Δ i is the actual deviation value of the i-th operation.

4. The empty cigarette storage management system according to claim 1, characterized in that: The intelligent cargo grid module includes a dynamic display module, an indicator light module and a sensing control module. The dynamic display module is used to display the zero-cigarette brand, real-time inventory, historical in and out records of the cargo grid and operation instructions. The indicator light module switches the lighting state in real time in response to system instructions based on a multi-color LED array. The sensing control module is used to monitor and control the cargo grid status, which includes a pressure sensor array and a capacitive touch button, which are respectively used to detect the zero-cigarette inventory, eliminate task instructions and identify cargo grid information.

5. The empty cigarette warehouse management system according to claim 1, characterized in that: The intelligent scheduling module includes a weight calculation module, a task redistribution module and an intelligent guidance module. The weight calculation module generates a dynamic picking path based on a real-time dynamic weight calculation model. The task redistribution module redistributes tasks between operators based on their real-time positions. The intelligent guidance module instructs operators to move and pick according to the dynamically updated planned path based on light projection.

6. The empty cigarette warehouse management system according to claim 5, characterized in that: The real-time dynamic weight calculation model performs nonlinear fitting on the cargo grid position coordinates (x, y, z) with the equipment load rate L and the environmental interference factor E to generate a path weight value, which is expressed as follows: W=α·f(x,y,z)+β·L+γ·E Among them, α, β, and γ are dynamic adjustment coefficients.

7. The empty cigarette storage management system according to claim 1, characterized in that: The hybrid verification process includes an initial inventory phase, a re-inventory phase, and a final inventory phase. The initial inventory phase automatically plans an S-shaped inventory route based on UWB positioning technology. The re-inventory phase detects abnormalities in the stacking of cigarettes in the cargo compartment based on millimeter-wave radar. The final inventory phase generates an inventory status heat map including a confidence score based on the positioning data of the initial inventory phase and the detection data of the re-inventory settlement.

8. The empty cigarette warehouse management system according to claim 1, characterized in that: The intelligent inventory module includes a cycle strategy generation module and a difference processing module. The cycle strategy generation module generates the inventory strategy of the intelligent cargo grid module based on the daily, weekly and monthly inventory frequencies. The difference processing module is used to automatically generate inventory adjustment instructions and attach the operator's digital signature.

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