CN117196467A - Intelligent warehouse shelf management system based on RFID technology - Google Patents
Intelligent warehouse shelf management system based on RFID technology Download PDFInfo
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Abstract
The invention discloses an intelligent warehouse shelf management system based on an RFID technology, which comprises a correlation module, a position acquisition module, a statistics updating module, an optimization management module and an automatic operation module, wherein the correlation module is used for establishing a database, correlating each article with a unique identifier, attaching an RFID label containing the unique identifier to the article correlated with the unique identifier, the position acquisition module is used for determining the real-time position of each article, the statistics updating module is used for acquiring and judging the shelf serial number of each article according to the real-time position of all articles at a preset frequency, recording the number of the articles corresponding to the shelf serial number and updating the database, the optimization management module is used for dynamically optimizing and managing the placement position of each article according to the change condition of the number of the articles corresponding to each shelf serial number in the database, and the automatic operation module is used for generating the behavior flow of an automatic robot according to the dynamic optimization management result. According to the invention, an RFID technology and an automatic robot are introduced to carry out intelligent management on the warehouse, so that the warehouse picking efficiency and accuracy are improved.
Description
Technical Field
The invention relates to the field of intelligent warehouse shelf management of RFID technology, in particular to an intelligent warehouse shelf management system based on RFID technology.
Background
With the development of globalization, the logistics and supply chain industries have become a key driving force for global economic development. The warehouse is an important link of logistics and supply chains, and the management efficiency of the warehouse directly influences the operation efficiency of the whole supply chain. However, in the conventional warehouse shelf management, the placement position of the goods is not effectively optimized, and often the placement is performed based on the time sequence of arriving goods, rather than the characteristics of the goods, which causes efficiency problems. And in the conventional warehouse shelf management, the goods are usually placed and taken manually, for example, the application number is as follows: 201910020250.4 the invention discloses a warehouse goods storage management system and a management method, wherein a management server in the management method judges the storage position of goods according to goods information, and prompts the goods storage material level of an forklift tool body through a mobile terminal.
Disclosure of Invention
The invention provides an intelligent warehouse goods shelf based on an RFID technology, which utilizes the RFID technology and an automatic robot to automatically put warehouse goods and is used for solving the problems of low operation efficiency and poor accuracy caused by the fact that goods are put in a warehouse in order and manual warehouse management is used in the prior art.
An intelligent warehouse rack based on RFID technology, the system comprising:
the association module is used for establishing a database, associating each article with a unique identifier, and attaching an RFID tag containing the unique identifier to the article associated with the unique identifier;
the position acquisition module is used for setting an RFID reader at each layer of the goods shelf at a preset distance, and determining the real-time position of each goods according to the RFID tag signals received by the RFID reader;
the statistics updating module is used for acquiring and judging the serial numbers of the goods where all the goods are located according to the real-time positions of the goods at preset frequency, recording the number of the goods corresponding to the serial numbers of the goods and updating the database;
the optimizing management module is used for dynamically optimizing and managing the placement position of each goods according to the change condition of the number of the goods corresponding to each goods shelf serial number in the database;
and the automatic operation module is used for generating a behavior flow of the automatic robot according to the dynamic optimization management result.
Preferably, the association module includes:
the database construction submodule is used for acquiring and constructing a database by using attribute information of different goods;
the first association sub-module is used for generating a unique identifier of each item according to the attribute information of each item, the information of the computing equipment when the identifier is generated and the random number generated by using a preset function and associating the item with the unique identifier;
An RFID tag generation sub-module for generating a plurality of RIFD tags associated with different items using different unique identifiers;
an attachment sub-module for attaching each RFID tag to an item associated with the RFID tag by means of a lanyard or glue.
Preferably, the location acquisition module includes:
the shelf segmentation submodule is used for determining the length of a shelf, and dividing each layer of the shelf into a plurality of equal-area areas according to the preset distance according to the length of the shelf;
the setting sub-module is used for setting RFID readers on the central axis of each divided area, and acquiring the positions of different RFID readers after the setting is completed;
the signal transmitting sub-module is used for continuously transmitting radio frequency signals through a plurality of RFID readers;
the selecting sub-module is used for acquiring a plurality of radio frequency signals received by the RFID tag of each commodity, determining an RFID reader sending out each radio frequency signal and selecting a target RFID reader with the strongest radio frequency signal intensity;
the signal feedback sub-module is used for sending a feedback signal containing a unique identifier to a target RFID reader of each commodity through the RFID tag of the commodity;
the position determining sub-module is used for receiving a plurality of feedback signals through a plurality of RFID readers and determining the position of the goods associated with each feedback signal received by the position determining sub-module according to the positions of different RFID readers.
Preferably, the statistical updating module includes:
the time acquisition sub-module is used for acquiring attribute information of different goods and obtaining the predicted turnover time of each goods according to the attribute information;
the time calculation sub-module is used for carrying out average calculation on the predicted turnover time of all the goods, and the obtained average is the predicted average turnover time of the whole goods;
the real-time acquisition sub-module is used for setting an updating period according to the average turnover time and periodically acquiring the real-time positions of all goods according to the updating period;
the goods shelf serial number obtaining sub-module is used for obtaining the goods shelf serial number of different goods at present according to the real-time position of each goods;
the counting sub-module is used for acquiring the number of goods under different shelf serial numbers;
and the updating sub-module is used for sending an updating instruction to the database for updating according to the real-time positions of all the goods and the quantity of the goods under different goods shelf serial numbers, and generating a database updating log.
The time acquisition sub-module is used for acquiring attribute information of different goods and obtaining the predicted turnover time of each goods according to the attribute information;
the time calculation sub-module is used for carrying out average calculation on the predicted turnover time of all the goods, and the obtained average is the predicted average turnover time of the whole goods;
The real-time acquisition sub-module is used for setting an updating period according to the average turnover time and periodically acquiring the real-time positions of all goods according to the updating period;
the goods shelf serial number obtaining sub-module is used for obtaining the goods shelf serial number of different goods at present according to the real-time position of each goods;
the counting sub-module is used for acquiring the number of goods under different shelf serial numbers;
and the updating sub-module is used for sending an updating instruction to the database for updating according to the real-time positions of all the goods and the quantity of the goods under different goods shelf serial numbers, and generating a database updating log.
Preferably, the optimization management module includes:
the sales frequency calculation sub-module is used for acquiring the update log of the database, acquiring the quantity change condition of each goods in the interval time by taking three months as the interval time, and calculating a quotient by using the quantity change condition of each goods and the interval time, wherein the quotient is the sales frequency of different goods;
the inventory quantity counting sub-module is used for searching the database and counting the inventory quantity of different goods;
the loading condition judging sub-module is used for obtaining loading conditions of different shelves according to the number of goods under different shelf serial numbers and marking the shelves with loading capacity larger than a preset loading proportion as full load;
The inter-shelf transfer sub-module is used for acquiring different goods attribute information, generating an inter-shelf transfer strategy according to the weight, the size, the class and the goods loading condition of different goods, and transferring the goods in the inter-shelf position;
the goods shelf inner transferring sub-module is used for generating a goods shelf inner transferring strategy according to the sales frequency and the inventory quantity of goods and transferring the goods in the goods shelf inner position;
the method generation submodule is used for generating a comprehensive dynamic optimization management method by using inter-shelf and intra-shelf transfer strategies.
Preferably, the automatic operation module includes:
the process generation submodule is used for sequentially decomposing the inter-shelf transfer strategy and the intra-shelf transfer strategy into independent steps, writing a plurality of task functions according to the independent steps, and combining the plurality of task functions to generate an automatic robot movement and operation process;
the flow execution sub-module is used for moving goods among different goods shelves and inside the goods shelves by controlling the actions of the automatic robot according to the moving and operating flow of the automatic robot;
the monitoring sub-module is used for monitoring the working condition and the running state of the automatic robot and carrying out abnormality judgment;
And the abnormality processing sub-module is used for generating an abnormality processing scheme and processing if the automatic robot is judged to have abnormality.
Preferably, the inter-shelf transfer sub-module includes:
the weight setting unit is used for acquiring the weight of each article according to the attribute information of each article, setting the article lower than the first kilogram as a low-weight article, and setting the article higher than the first kilogram as a high-weight article;
the size setting unit is used for acquiring the size of each article according to the attribute information of each article, setting the article with the length of any side not longer than the first centimeter as a small-size article, setting the article with the length of any side longer than the first centimeter and shorter than the second centimeter as a medium-size article, and setting the article with the length of any side longer than the second centimeter as a large-size article;
the article setting unit is used for acquiring each article function according to each article attribute information and setting all article types according to each article function;
the first transfer unit is used for acquiring and judging the loading condition of each goods shelf, if the target goods shelf is judged to be full, skipping over the goods shelf until the goods shelf which is not full is found, placing different goods on the goods shelf which is not full according to the principle that the same goods shelf is only placed with the same goods, placing the goods with high weight and large size at the two layers at the bottom of the goods shelf at the same time, and randomly placing the combination of the rest weight and the size.
Preferably, the intra-shelf transfer module includes:
the sales frequency marking unit is used for obtaining the expected sales frequency of different goods, comparing the expected sales frequency of different goods with a preset sales frequency threshold, marking the goods as easy-to-sell goods if the expected sales frequency of one goods is higher than or equal to the preset sales frequency threshold, and marking the goods as difficult-to-sell goods if the expected sales frequency of one goods is lower than the preset sales frequency threshold;
the stock quantity marking unit is used for obtaining stock quantities of different goods and calculating the stock quantities and corresponding sales frequency as quotient values to obtain the turnover number of different goods, marking the goods as high stock quantity goods if the turnover number of one goods is greater than or equal to the preset turnover number of days, and marking the goods as low stock quantity goods if the turnover number of one goods is less than the preset turnover number of days;
a scoring unit for scoring each of the articles in combination according to the sales frequency and the inventory quantity, scoring a first article marked as a easily-sold article and a low-inventory article as the highest, scoring a second article marked as a easily-sold article and a high-inventory article as the next highest, scoring a third article marked as a difficult-to-sell article and a low-inventory article as the medium, and scoring a fourth article marked as a difficult-to-sell article and a high-inventory article as the low;
And a second transfer unit for placing all the articles except the articles of high weight and large size at the same time from the upper left corner of the shelf according to the assigned articles from high to low.
Preferably, the monitoring sub-module includes:
the recording unit is used for recording the accuracy of placing the goods to the target area each time by the automatic robot by using the camera;
the acquisition unit is used for monitoring the hardware state of the automatic robot in real time by using preset software, and simultaneously monitoring the software operation log in real time;
the first abnormality judging unit is used for judging whether the accuracy of placing the goods to the target area in the time period reaches the preset accuracy or not in each hour by the automatic robot, and if not, marking the state of the automatic robot as abnormal, and generating a first abnormality instruction;
and the second abnormality judging unit is used for judging whether the hardware report and the software operation log of the automatic robot have errors or not, and if so, generating a second abnormality instruction.
Preferably, in generating the unique identifier for each item, the system is further configured to:
obtaining a class code of each item;
symmetrically encrypting the class code of each goods, and converting the class code into binary by using a preset conversion function; setting a self-defining time as a first time;
Acquiring a second moment generated when the class code of each goods is symmetrically encrypted;
calculating a difference value between the second moment and the first moment, obtaining a moment difference value of each goods, converting units of the moment difference value into seconds, and converting the seconds into binary by using a preset conversion function;
acquiring the utilization rate of a central processor and a display card of computing equipment for symmetrically encrypting each goods at a second moment, and carrying out addition calculation on the utilization rate of the central processor and the display card to obtain a sum value;
creating a random number generation function, and taking the sum value as a first initial input of the random number generation function;
adding the class code of the symmetrically encrypted goods after the first initial input to obtain a second initial input;
generating a random number corresponding to each article by taking the second initial input as an actual initial input of a random number generation function and converting the random number into binary by using a preset conversion function;
and (3) symmetrically encrypting and converting each goods into binary goods codes, binary-converted time difference values corresponding to each goods, combining binary-converted random numbers corresponding to each goods to generate a unique identifier of each goods, and using a special binary symbol as a separator.
Through the technical scheme, the invention has the following beneficial effects:
1) The goods are placed according to the goods types, the sales frequency and the stock quantity, so that the efficiency of the goods in the process of delivering the goods out of the warehouse is improved, and a large amount of time is saved;
2) The automatic robot is used for placing goods between the goods shelves and in the goods shelves according to the automatically generated flow, so that the accuracy of placing the goods is improved, and placing errors caused by human factors are avoided.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of a system for intelligent warehouse shelf management based on RFID technology in an embodiment of the invention;
Fig. 2 is a schematic structural diagram of an association module of an intelligent warehouse shelf management system based on an RFID technology in an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a location acquisition module of an intelligent warehouse shelf management system based on an RFID technology in an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
With the development of globalization, the logistics and supply chain industries have become a key driving force for global economic development. The warehouse is an important link of logistics and supply chains, and the management efficiency of the warehouse directly influences the operation efficiency of the whole supply chain. However, in the conventional warehouse shelf management, the placement position of the goods is not effectively optimized, and often the placement is performed based on the time sequence of arriving goods, rather than the characteristics of the goods, which causes efficiency problems. And in the conventional warehouse shelf management, the goods are usually placed and taken manually, for example, the application number is as follows: 201910020250.4 the invention discloses a warehouse goods storage management system and a management method, wherein a management server in the management method judges the storage position of goods according to goods information, and prompts the goods storage material level of an forklift tool body through a mobile terminal. In order to solve the problems, the embodiment discloses an intelligent warehouse shelf management system based on an RFID technology.
Example 1
The embodiment provides an intelligent warehouse shelf management system based on RFID technology, as shown in FIG. 1, comprising:
an association module 101 for creating a database, associating each item with a unique identifier, and attaching an RFID tag containing the unique identifier to the item associated therewith;
the position acquisition module 102 is configured to set an RFID reader at a preset distance on each layer of the shelf, and determine a real-time position of each item according to an RFID tag signal received by the RFID reader;
the statistics updating module 103 is used for acquiring and judging the serial numbers of the goods where all the goods are located according to the real-time positions of the goods at preset frequency, recording the number of the goods corresponding to the serial numbers of the goods and updating the database;
the optimizing management module 104 is configured to dynamically optimize and manage a placement position of each item according to a variation condition of the item number corresponding to each shelf serial number in the database;
and the automatic operation module 105 is used for generating a behavior flow of the automatic robot according to the dynamic optimization management result.
In this embodiment, the unique identifier refers to a composition of a random number separator, using the item class code of the item itself, calculating the time difference between the second time at which the unique identifier is calculated and the preset first time
In this embodiment, the database established is a mysql database;
in this embodiment, the unique identifier is unique in the present system and is not globally unique;
in this embodiment, the attached finger RFID tag is attached to the article and does not come off in the case of non-rapid movement;
in this embodiment, the RFID tag workflow is to send a feedback signal containing a unique identifier after receiving a radio frequency signal sent by an RFID reader;
in this embodiment, the location of each item is the location of the RFID reader that received the unique identifier associated with the item;
in this embodiment, dynamic optimization management refers to dynamic transfer of items according to the generated inter-shelf and intra-shelf transfer policies.
The working principle of the technical scheme is as follows: through the association module 101, a database is established, each article is associated with a unique identifier, an RFID tag containing the unique identifier is attached to the article associated with the article, an RFID reader is arranged on each layer of the article shelf at a preset distance through the position acquisition module 102, the real-time position of each article is determined according to the RFID tag signals received by the RFID reader, the article shelf serial numbers of the article are acquired at a preset frequency and judged according to all the article shelf real-time positions through the statistics updating module 103, the article number corresponding to the article shelf serial numbers is recorded and the database is updated, dynamic optimization management is carried out on the placing position of each article according to the change condition of the article number corresponding to the article shelf serial numbers in the database through the optimization management module 104, and the behavior flow of the automatic robot is generated according to the dynamic optimization management result through the automatic operation module 105.
The beneficial effects of the technical scheme are that: the automatic goods loading and unloading device has the advantages that the goods are loaded and unloaded according to the characteristics of the goods, the time required for searching during loading and unloading is reduced, a path can be generated faster, the problem that the loading and unloading efficiency is low due to the fact that goods are loaded and unloaded according to the warehouse-in time is solved, and the automatic robot is used for moving and operating the goods, so that the automatic robot is precise in structure and high in operation precision, the loading errors caused by human factors are solved, the loading accuracy is improved, the warehouse management efficiency is effectively improved, and the supply chain operation efficiency is further improved.
Example 2
On the basis of embodiment 1, the intelligent warehouse shelf management system based on the RFID technology, the association module 101 includes:
a database construction sub-module 1011 for acquiring and constructing a database using attribute information of different goods;
a first association sub-module 1012 for generating a unique identifier of each item according to each item attribute information, information of the computing device at the time of generating the identifier, and a random number generated using a preset function and associating the item with the unique identifier thereof;
an RFID tag generation sub-module 1013 for generating a plurality of RIFD tags associated with different items using different unique identifiers;
An attachment sub-module 1014 is used to attach each RFID tag to the item associated with the RFID tag by means of a lanyard or glue.
In this embodiment, the attribute information of the article includes: the predicted turn-around time, weight, size, type of the good;
in this embodiment, the information of the computing device when generating the identifier includes a difference between a time of the computing device when generating the identifier and a preset first time and a physical address of the computing device;
in this embodiment, the predetermined function is a random number generation function;
in this embodiment, a lanyard or glue is used in order not to cause the RFID tag to fall out due to the rapid movement of the article when the RFID tag is attached to the article.
The beneficial effects of the technical scheme are as follows: the database is constructed by acquiring and using the attribute information of different goods, so that the searching efficiency when the attribute information of different goods is utilized later is improved, the efficiency when the goods are put and taken is improved by generating a plurality of unique identifiers related to different goods according to a plurality of kinds of information, and the attaching stability is improved by attaching each RFID label to the goods related to the RFID label in a rope hanging or glue manner.
Example 3
On the basis of embodiment 1, the intelligent warehouse shelf management system based on RFID technology, the location acquisition module 102 includes:
the shelf segmentation submodule 1021 is used for determining the length of a shelf, and dividing each layer of the shelf into a plurality of equal-area areas according to the preset distance according to the length of the shelf;
a setting sub-module 1022, configured to set an RFID reader on a central axis of each of the divided areas, and obtain positions of different RFID readers after the setting is completed;
a signal transmitting sub-module 1023 for continuously transmitting radio frequency signals through a plurality of RFID readers;
a selection submodule 1024, configured to acquire a plurality of radio frequency signals received by the RFID tag of each item, determine an RFID reader that sends out each radio frequency signal, and select a target RFID reader with the strongest radio frequency signal strength;
a signal feedback sub-module 1025 for transmitting a feedback signal containing a unique identifier to a target RFID reader of each item through the RFID tag of the item;
the location determining submodule 1026 is configured to receive a plurality of feedback signals through a plurality of RFID readers, and determine a location of an item associated with each feedback signal received by the location determining submodule according to different RFID reader locations.
In this embodiment, the warehouse shelf length is a multiple of 200 cm, so the preset distance may be set here to 200 cm;
in this embodiment, the RFID reader location includes the shelf serial number and the shelf division area location;
in this embodiment, the radio frequency signal is a radio signal, and is mainly used for wireless communication between devices;
in this embodiment, the reason why the RFID tag needs to select the target RFID reader with the strongest radio frequency signal intensity is that the RFID tag is in the range of radio frequency signals sent by a plurality of RFID readers, and the strongest signal intensity represents that the RFID tag is closest to the RFID reader;
in this embodiment, the feedback signal refers to a signal transmitted by the RFID tag after receiving a radio frequency signal transmitted by the RFID reader.
The beneficial effects of the technical scheme are as follows: through splitting each layer of the shelf by a preset distance according to the length of the shelf, the position of the RFID reader is conveniently determined later, and the RFID reader is arranged on the central axis of each shelf splitting area, so that each RFID tag can judge the position of the RFID tag according to the intensity of radio frequency signals of different RFID readers, and the RFID tag sends a feedback signal after receiving the radio frequency signals, thereby reducing energy loss, selecting the target RFID reader with the strongest radio frequency signal intensity, and being capable of selecting the RFID reader closest to the RFID tag at the highest speed.
Example 4
On the basis of embodiment 1, the intelligent warehouse shelf management system based on the RFID technology, the statistics update module includes:
the time acquisition sub-module is used for acquiring attribute information of different goods and obtaining the predicted turnover time of each goods according to the attribute information;
the time calculation sub-module is used for carrying out average calculation on the predicted turnover time of all the goods, and the obtained average is the predicted average turnover time of the whole goods;
the real-time acquisition sub-module is used for setting an updating period according to the average turnover time and periodically acquiring the real-time positions of all goods according to the updating period;
the goods shelf serial number obtaining sub-module is used for obtaining the goods shelf serial number of different goods at present according to the real-time position of each goods;
the counting sub-module is used for acquiring the number of goods under different shelf serial numbers;
and the updating sub-module is used for sending an updating instruction to the database for updating according to the real-time positions of all the goods and the quantity of the goods under different goods shelf serial numbers, and generating a database updating log.
In this embodiment, the predicted turnaround time of each item is predicted in advance based on the historical big data;
In the embodiment, the reason that average calculation is performed on the predicted turnover time of all the goods is that the whole goods turnover speed can be reflected, and the influence of the extreme value on the whole goods turnover speed is reduced;
in the embodiment, the update instruction comprises real-time positions of all goods, the quantity information of the goods under different goods shelf serial numbers and database update instructions;
in this embodiment, the database update log is regenerated each time the database information changes.
The beneficial effects of the technical scheme are as follows: the average turnover time of the whole goods is used for obtaining the serial numbers of the goods where different goods are currently located in real time, so that the update frequency is effectively reduced, the calculation resources are saved, the historical data can be conveniently inquired and the problems can be conveniently tracked by generating the database update log, and the usability and maintainability are improved.
Example 5
On the basis of embodiment 1, the intelligent warehouse shelf management system based on the RFID technology, the optimization management module includes:
the sales frequency calculation sub-module is used for acquiring the update log of the database, acquiring the quantity change condition of each goods in the interval time by taking three months as the interval time, and calculating a quotient by using the quantity change condition of each goods and the interval time, wherein the quotient is the sales frequency of different goods;
The inventory quantity counting sub-module is used for searching the database and counting the inventory quantity of different goods;
the loading condition judging sub-module is used for obtaining loading conditions of different shelves according to the number of goods under different shelf serial numbers and marking the shelves with loading capacity larger than a preset loading proportion as full load;
the inter-shelf transfer sub-module is used for acquiring different goods attribute information, generating an inter-shelf transfer strategy according to the weight, the size, the class and the goods loading condition of different goods, and transferring the goods in the inter-shelf position;
and the goods shelf inner position transfer sub-module is used for generating a goods shelf inner position transfer strategy according to the sales frequency and the inventory quantity of goods.
In this embodiment, the reason for the interval of three months is that three months may be exactly one quarter or include sales data for two quarters, more typically;
in the embodiment, the reason for judging the loading condition is to prevent the overload risk of the goods shelf, so that the safety coefficient in the operation process is improved;
in this embodiment, the reason why the goods are transferred between shelves is that the goods of the same category need to be placed on the same shelf;
In this embodiment, the inter-shelf transfer strategy refers to the total process of moving the goods between the shelves generated according to the weights, sizes, types and loading conditions of different goods;
in this embodiment, the preset loading ratio is set at 95% here;
in this embodiment, the intra-shelf transfer strategy refers to the overall flow of movement of the items within the shelf generated based on the frequency of sales and inventory quantity of the items.
The beneficial effects of the technical scheme are as follows: the method has the advantages that the three months are taken as interval time, the change condition of the quantity of each goods in the interval time is obtained, and as the three months are taken as interval time, the change condition of the quantity of each goods in one quarter or two quarters can be represented, the accuracy of the sales frequency calculated later is improved, the loading condition of the goods shelf is judged, the overload risk of the goods shelf can be prevented, the safety coefficient in the operation process is improved, the goods are transferred between the goods shelves first and then are transferred inside the goods shelves, and the operation efficiency can be effectively improved.
Example 6
On the basis of embodiment 1, the intelligent warehouse shelf management system based on the RFID technology, the automatic operation module includes:
the process generation submodule is used for sequentially decomposing the inter-shelf transfer strategy and the intra-shelf transfer strategy into independent steps, writing a plurality of task functions according to the independent steps, and combining the plurality of task functions to generate an automatic robot movement and operation process;
The flow execution sub-module is used for moving goods among different goods shelves and inside the goods shelves by controlling the actions of the automatic robot according to the moving and operating flow of the automatic robot;
the monitoring sub-module is used for monitoring the working condition and the running state of the automatic robot and carrying out abnormality judgment;
and the abnormality processing sub-module is used for generating an abnormality processing scheme and processing if the automatic robot is judged to have abnormality.
In this embodiment, the purpose of decomposing the dynamic optimization management method into individual steps is to decompose one big task into a plurality of small tasks, so as to facilitate the programming implementation later;
in this embodiment, the task functions are implemented by programming the individual step pairs, and each task function performs a specific task, such as navigating to a target shelf and carrying a target commodity;
in this embodiment, the robotic operational procedures include, but are not limited to, rotate, grasp, put down;
in this embodiment, the exception handling scheme refers to a solution generated for existing exceptions, and is divided into two types, one of which requires an engineer to perform operation repair and one of which performs repair through self-regulation;
in this embodiment, anomalies include, but are not limited to, path anomalies, grasp anomalies, RFID tag scanning anomalies;
The beneficial effects of the technical scheme are as follows: the dynamic optimization management method is decomposed into independent steps, so that the later programming realization efficiency can be effectively improved, the automatic robot is used for executing the inter-shelf transfer strategy and the intra-shelf transfer strategy, the goods placement accuracy is improved, the automatic robot is subjected to anomaly monitoring and judgment, and the running stability of the automatic robot is improved.
Example 7
Based on embodiment 5, the intelligent warehouse shelf management system based on RFID technology, the inter-shelf transfer sub-module includes:
the weight setting unit is used for acquiring the weight of each article according to the attribute information of each article, setting the article lower than the first kilogram as a low-weight article, and setting the article higher than the first kilogram as a high-weight article;
the size setting unit is used for acquiring the size of each article according to the attribute information of each article, setting the article with the length of any side not longer than the first centimeter as a small-size article, setting the article with the length of any side longer than the first centimeter and shorter than the second centimeter as a medium-size article, and setting the article with the length of any side longer than the second centimeter as a large-size article;
The article setting unit is used for acquiring each article function according to each article attribute information and setting all article types according to each article function;
the first transfer unit is used for acquiring and judging the loading condition of each goods shelf, if the target goods shelf is judged to be full, skipping over the goods shelf until the goods shelf which is not full is found, placing different goods on the goods shelf which is not full according to the principle that the same goods shelf is only placed with the same goods, placing the goods with high weight and large size at the two layers at the bottom of the goods shelf at the same time, and randomly placing the combination of the rest weight and the size.
In this embodiment, the first kilogram may be set to 20 kilograms here;
in this embodiment, the first centimeter may be set to 50 centimeters herein;
in this embodiment, the second centimeter may be set to 100 centimeters here;
in this embodiment, the reason for placing the high weight and large size article on the bottom two layers of the shelf is that the probability of problems is greater when it is placed;
in this embodiment, the total goods include, but are not limited to, foods, household appliances, health beauty and consumer goods.
The beneficial effects of the technical scheme are as follows: only placing the goods of same class with same goods shelves, improved the searching efficiency when taking, with high weight and jumbo size goods place in goods shelves first, two-layer, reduced the risk that takes high weight and jumbo size goods to take probably take place.
Example 8
On the basis of embodiment 5, the intelligent warehouse shelf management system based on the RFID technology, the intra-shelf transfer module includes:
the sales frequency marking unit is used for obtaining the expected sales frequency of different goods, comparing the expected sales frequency of different goods with a preset sales frequency threshold, marking the goods as easy-to-sell goods if the expected sales frequency of one goods is higher than or equal to the preset sales frequency threshold, and marking the goods as difficult-to-sell goods if the expected sales frequency of one goods is lower than the preset sales frequency threshold;
the stock quantity marking unit is used for obtaining stock quantities of different goods and calculating the stock quantities and corresponding sales frequency as quotient values to obtain the turnover number of different goods, marking the goods as high stock quantity goods if the turnover number of one goods is greater than or equal to the preset turnover number of days, and marking the goods as low stock quantity goods if the turnover number of one goods is less than the preset turnover number of days;
a scoring unit for scoring each of the articles in combination according to the sales frequency and the inventory quantity, scoring a first article marked as a easily-sold article and a low-inventory article as the highest, scoring a second article marked as a easily-sold article and a high-inventory article as the next highest, scoring a third article marked as a difficult-to-sell article and a low-inventory article as the medium, and scoring a fourth article marked as a difficult-to-sell article and a high-inventory article as the low;
And a second transfer unit for placing all the articles except the articles of high weight and large size at the same time from the upper left corner of the shelf according to the assigned articles from high to low.
In this embodiment, the estimated sales frequency is estimated for using past sales results;
in this embodiment, the preset sales frequency threshold may be set at 50 pieces per day;
in this embodiment, the preset turnaround days may be set to 45 days here;
in this embodiment, the first article may be assigned a score of 4, the second article may be assigned a score of 3, the third article may be assigned a score of 2, and the fourth article may be assigned a score of 1;
in this embodiment, the reason why the high weight is not transferred and the size is large at the same time is to improve the stability of the shelf;
in this embodiment, the reason why the placement is performed according to the assigned height of the article is that the article with higher assigned score indicates a higher demand and a smaller stock quantity, and needs to be placed in a position easy to take.
The beneficial effects of the technical scheme are as follows: the goods with different sales frequencies and stock quantity are assigned, so that different goods can be selected when being placed and ordered later, the goods with high weight and large size are fixed on the first layer and the second layer of the goods shelf, and the safety and the stability of the goods shelf are improved.
Example 9
Based on embodiment 6, the intelligent warehouse shelf management system based on RFID technology, the monitoring sub-module includes:
the recording unit is used for recording the accuracy of placing the goods to the target area each time by the automatic robot by using the camera;
the acquisition unit is used for monitoring the hardware state of the automatic robot in real time by using preset software, and simultaneously monitoring the software operation log in real time;
the first abnormality judging unit is used for judging whether the accuracy of placing the goods to the target area in the time period reaches the preset accuracy or not in each hour by the automatic robot, and if not, marking the state of the automatic robot as abnormal, and generating a first abnormality instruction;
and the second abnormality judging unit is used for judging whether the hardware report and the software operation log of the automatic robot have errors or not, and if so, generating a second abnormality instruction.
In this embodiment, the preset software functions to acquire information such as temperature, electric quantity, speed, etc. of the hardware of the automatic robot in real time;
in this embodiment, the automated robotic hardware includes, but is not limited to, an electric motor, a controller;
in this embodiment, the software running log includes steps executed by the automated robot, user operation records, and software running error reports;
In this embodiment, the preset accuracy is 98%;
in this embodiment, in recording the accuracy of placing the article to the target area each time by the automated robot using the camera, it includes:
marking each layer of the goods shelf with accurate scales;
configuring a high-resolution camera at the top of an automatic robot working area;
a preset synchronization program is used for realizing synchronous starting of the high-resolution camera and the automatic robot;
sending a carrying command to the automatic robot for a plurality of times;
in the carrying process after the automatic robot receives carrying commands each time, continuously recording the whole carrying process through a high-resolution camera to obtain a plurality of recorded data;
dividing each record data into position movement record data and mechanical arm movement record data through a preset machine learning model;
analyzing the carrying command into a position moving command and a mechanical arm moving command through a preset command analysis function, and analyzing the position moving command and the mechanical arm moving command to obtain a target moving position and a target mechanical arm moving position;
the position movement record data and the mechanical arm movement record data are respectively input into a preset analysis model,
Obtaining a first actual moving position and a first actual mechanical arm moving position;
calculating a difference value between the first actual moving position and the target moving position, and taking the obtained first difference value as a first error;
calculating a difference value between the first actual mechanical arm moving position and the target mechanical arm moving position, and taking the obtained second difference value as a second error;
if the first error and the second error are both higher than a preset error threshold value, acquiring an automatic robot moving device and a mechanical arm, and configuring controllers with preset control functions on the automatic robot moving device and the mechanical arm;
correcting the automatic robot moving device and the mechanical arm according to the first error and the second error by using a controller with a preset control function;
placing the automatic robot at a position before executing the carrying command, and re-executing the position moving command and the mechanical arm moving command in the carrying command to obtain target record data;
dividing target record data into target position movement record data and target mechanical arm movement record data through a preset machine learning model;
respectively inputting the target position movement record data and the target mechanical arm movement record data into a preset analysis model to obtain a second actual movement position and a second actual mechanical arm movement position;
Calculating a difference value between the second actual moving position and the target moving position, and taking the obtained third difference value as a third error;
calculating a difference between the moving position of the two actual mechanical arms and the moving position of the target mechanical arm, and taking the obtained fourth difference as a fourth error;
drawing a third error into a first folding line diagram, and marking a preset error threshold value on the first folding line diagram;
drawing a fourth error into a second folding line graph, and marking a preset error threshold value on the second folding line graph;
the first and second fold lines are used as a basis for subsequent judgment of the accuracy of the automated robot.
The beneficial effects of the technical scheme are as follows: the working result of the automatic robot is recorded and judged by using the camera, the comprehensive state of the automatic robot can be effectively judged, the automatic robot is monitored in real time by software and hardware, the automatic robot can be processed in time when the automatic robot is in primary error, and the reliability of the running process is improved.
Example 10
In one embodiment, in generating the unique identifier for each item, the system is further configured to:
obtaining a class code of each item;
symmetrically encrypting the class code of each goods, and converting the class code into binary by using a preset conversion function; setting a self-defining time as a first time;
Acquiring a second moment generated when the class code of each goods is symmetrically encrypted;
calculating a difference value between the second moment and the first moment, obtaining a moment difference value of each goods, converting units of the moment difference value into seconds, and converting the seconds into binary by using a preset conversion function;
when the computing equipment symmetrically encrypts each goods at the second moment, the utilization rate of the central processor and the display card is obtained, and the utilization rate of the central processor and the display card is subjected to addition calculation to obtain a sum value;
creating a random number generation function, and taking the sum value as a first initial input of the random number generation function;
adding the class code of the symmetrically encrypted goods after the first initial input to obtain a second initial input;
the second initial input is used as the actual initial input of a random number generation function, a random number is generated, and the random number is converted into binary by using a preset conversion function;
each item is symmetrically encrypted and converted to a binary item class code, the binary converted time difference value and the binary converted random number are combined to generate a unique identifier of each item, and a special binary symbol is used as a separator.
In this embodiment, the class code of the article is a code classified according to the function of the article;
in this embodiment, the symmetric encryption refers to encryption and decryption using one key;
in this embodiment, the preset conversion function is to convert various data into ASCII codes first, and then convert corresponding ASCII codes into binary;
in this embodiment, the custom time is not later than the second time, here set to 1 month 1 day 1970;
in this embodiment, the specific binary character may be set to "01111100" herein, i.e., "|" in ASCII encoding.
The beneficial effects of the technical scheme are as follows: by generating the unique identifier according to the class code of each article, the time difference corresponding to each article and the random number corresponding to each article, the uniqueness of the identifier is ensured, and errors in recognition and calculation are avoided.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. An intelligent warehouse shelf management system based on an RFID technology, the system comprising:
the association module is used for establishing a database, associating each article with a unique identifier, and attaching an RFID tag containing the unique identifier to the article associated with the unique identifier;
the position acquisition module is used for setting an RFID reader at each layer of the goods shelf at a preset distance, and determining the real-time position of each goods according to the RFID tag signals received by the RFID reader;
the statistics updating module is used for acquiring and judging the serial numbers of the goods where all the goods are located according to the real-time positions of the goods at preset frequency, recording the number of the goods corresponding to the serial numbers of the goods and updating the database;
the optimizing management module is used for dynamically optimizing and managing the placement position of each goods according to the change condition of the number of the goods corresponding to each goods shelf serial number in the database;
and the automatic operation module is used for generating a behavior flow of the automatic robot according to the dynamic optimization management result.
2. The intelligent warehouse rack management system based on RFID technology of claim 1, wherein the association module comprises:
the database construction submodule is used for acquiring and constructing a database by using attribute information of different goods;
the first association sub-module is used for generating a unique identifier of each item according to the attribute information of each item, the information of the computing equipment when the identifier is generated and the random number generated by using a preset function and associating the item with the unique identifier;
an RFID tag generation sub-module for generating a plurality of RIFD tags associated with different items using different unique identifiers;
an attachment sub-module for attaching each RFID tag to an item associated with the RFID tag by means of a lanyard or glue.
3. The intelligent warehouse rack management system based on RFID technology as claimed in claim 1, wherein the location acquisition module comprises:
the shelf segmentation submodule is used for determining the length of a shelf, and dividing each layer of the shelf into a plurality of equal-area areas according to the preset distance according to the length of the shelf;
the setting sub-module is used for setting RFID readers on the central axis of each divided area, and acquiring the positions of different RFID readers after the setting is completed;
The signal transmitting sub-module is used for continuously transmitting radio frequency signals through a plurality of RFID readers;
the selecting sub-module is used for acquiring a plurality of radio frequency signals received by the RFID tag of each commodity, determining an RFID reader sending out each radio frequency signal and selecting a target RFID reader with the strongest radio frequency signal intensity;
the signal feedback sub-module is used for sending a feedback signal containing a unique identifier to a target RFID reader of each commodity through the RFID tag of the commodity;
the position determining sub-module is used for receiving a plurality of feedback signals through a plurality of RFID readers and determining the position of the goods associated with each feedback signal received by the position determining sub-module according to the positions of different RFID readers.
4. The intelligent warehouse rack management system based on RFID technology of claim 1, wherein the statistics update module comprises:
the time acquisition sub-module is used for acquiring attribute information of different goods and obtaining the predicted turnover time of each goods according to the attribute information;
the time calculation sub-module is used for carrying out average calculation on the predicted turnover time of all the goods, and the obtained average is the predicted average turnover time of the whole goods;
The real-time acquisition sub-module is used for setting an updating period according to the average turnover time and periodically acquiring the real-time positions of all goods according to the updating period;
the goods shelf serial number obtaining sub-module is used for obtaining the goods shelf serial number of different goods at present according to the real-time position of each goods;
the counting sub-module is used for acquiring the number of goods under different shelf serial numbers;
and the updating sub-module is used for sending an updating instruction to the database for updating according to the real-time positions of all the goods and the quantity of the goods under different goods shelf serial numbers, and generating a database updating log.
5. The intelligent warehouse rack management system based on RFID technology of claim 1, wherein the optimization management module comprises:
the sales frequency calculation sub-module is used for acquiring the update log of the database, acquiring the quantity change condition of each goods in the interval time by taking three months as the interval time, and calculating a quotient by using the quantity change condition of each goods and the interval time, wherein the quotient is the sales frequency of different goods;
the inventory quantity counting sub-module is used for searching the database and counting the inventory quantity of different goods;
the loading condition judging sub-module is used for obtaining loading conditions of different shelves according to the number of goods under different shelf serial numbers and marking the shelves with loading capacity larger than a preset loading proportion as full load;
The inter-shelf transfer sub-module is used for acquiring different goods attribute information, generating an inter-shelf transfer strategy according to the weight, the size, the class and the goods loading condition of different goods, and transferring the goods in the inter-shelf position;
and the goods shelf inner position transfer sub-module is used for generating a goods shelf inner position transfer strategy according to the sales frequency and the inventory quantity of goods.
6. The intelligent warehouse rack management system based on RFID technology as claimed in claim 1, wherein the automated operation module comprises:
the process generation submodule is used for sequentially decomposing the inter-shelf transfer strategy and the intra-shelf transfer strategy into independent steps, writing a plurality of task functions according to the independent steps, and combining the plurality of task functions to generate an automatic robot movement and operation process;
the flow execution sub-module is used for moving goods among different goods shelves and inside the goods shelves by controlling the actions of the automatic robot according to the moving and operating flow of the automatic robot;
the monitoring sub-module is used for monitoring the working condition and the running state of the automatic robot and carrying out abnormality judgment;
And the abnormality processing sub-module is used for generating an abnormality processing scheme and processing if the automatic robot is judged to have abnormality.
7. The intelligent warehouse rack management system based on RFID technology as claimed in claim 5, wherein the inter-rack transfer sub-module comprises:
the weight setting unit is used for acquiring the weight of each article according to the attribute information of each article, setting the article lower than the first kilogram as a low-weight article, and setting the article higher than the first kilogram as a high-weight article;
the size setting unit is used for acquiring the size of each article according to the attribute information of each article, setting the article with the length of any side not longer than the first centimeter as a small-size article, setting the article with the length of any side longer than the first centimeter and shorter than the second centimeter as a medium-size article, and setting the article with the length of any side longer than the second centimeter as a large-size article;
the article setting unit is used for acquiring each article function according to each article attribute information and setting all article types according to each article function;
the first transfer unit is used for acquiring and judging the loading condition of each goods shelf, if the target goods shelf is judged to be full, skipping over the goods shelf until the goods shelf which is not full is found, placing different goods on the goods shelf which is not full according to the principle that the same goods shelf is only placed with the same goods, placing the goods with high weight and large size at the two layers at the bottom of the goods shelf at the same time, and randomly placing the combination of the rest weight and the size.
8. The intelligent warehouse rack management system based on the RFID technology as claimed in claim 5, wherein the rack transfer module comprises
The sales frequency marking unit is used for obtaining the expected sales frequency of different goods, comparing the expected sales frequency of different goods with a preset sales frequency threshold, marking the goods as easy-to-sell goods if the expected sales frequency of one goods is higher than or equal to the preset sales frequency threshold, and marking the goods as difficult-to-sell goods if the expected sales frequency of one goods is lower than the preset sales frequency threshold;
the stock quantity marking unit is used for obtaining stock quantities of different goods and calculating the stock quantities and corresponding sales frequency as quotient values to obtain the turnover number of different goods, marking the goods as high stock quantity goods if the turnover number of one goods is greater than or equal to the preset turnover number of days, and marking the goods as low stock quantity goods if the turnover number of one goods is less than the preset turnover number of days;
a scoring unit for scoring each of the articles in combination according to the sales frequency and the inventory quantity, scoring a first article marked as a easily-sold article and a low-inventory article as the highest, scoring a second article marked as a easily-sold article and a high-inventory article as the next highest, scoring a third article marked as a difficult-to-sell article and a low-inventory article as the medium, and scoring a fourth article marked as a difficult-to-sell article and a high-inventory article as the low;
And a second transfer unit for placing all the articles except the articles of high weight and large size at the same time from the upper left corner of the shelf according to the assigned articles from high to low.
9. The intelligent warehouse rack management system based on RFID technology as claimed in claim 6, wherein the monitoring sub-module comprises:
the recording unit is used for recording the accuracy of placing the goods to the target area each time by the automatic robot by using the camera;
the acquisition unit is used for monitoring the hardware state of the automatic robot in real time by using preset software, and simultaneously monitoring the software operation log in real time;
the first abnormality judging unit is used for judging whether the accuracy of placing the goods to the target area in the time period reaches the preset accuracy or not in each hour by the automatic robot, and if not, marking the state of the automatic robot as abnormal, and generating a first abnormality instruction;
and the second abnormality judging unit is used for judging whether the hardware report and the software operation log of the automatic robot have errors or not, and if so, generating a second abnormality instruction.
10. The intelligent warehouse rack management system based on RFID technology as claimed in claim 2, further comprising, in generating a unique identifier for each item:
Obtaining a class code of each item;
symmetrically encrypting the class code of each goods, and converting the class code into binary by using a preset conversion function;
setting a self-defining time as a first time;
acquiring a second moment generated when the class code of each goods is symmetrically encrypted;
calculating a difference value between the second moment and the first moment, obtaining a moment difference value of each goods, converting units of the moment difference value into seconds, and converting the seconds into binary by using a preset conversion function;
when the computing equipment symmetrically encrypts each goods at the second moment, the utilization rate of the central processor and the display card is obtained, and the utilization rate of the central processor and the display card is subjected to addition calculation to obtain a sum value;
creating a random number generation function, and taking the sum value as a first initial input of the random number generation function;
adding the class code of the symmetrically encrypted goods after the first initial input to obtain a second initial input;
the second initial input is used as the actual initial input of a random number generation function, a random number is generated, and the random number is converted into binary by using a preset conversion function;
each item is symmetrically encrypted and converted to a binary item class code, the binary converted time difference value and the binary converted random number are combined to generate a unique identifier of each item, and a special binary symbol is used as a separator.
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