Warehouse management method, system, electronic device and computer readable storage medium

Abstract

The application discloses a warehouse management method and system, an electronic device and a computer readable storage medium, relates to the technical field of warehouse management, and comprises the following steps: acquiring a robot to be predicted; acquiring operation data of the robot from a preset operation and maintenance system; the operation data comprises time data and execution data; according to the time data and the execution data, the remaining life of each component to be predicted of the robot is calculated; when the remaining life is less than a preset threshold value, life warning is performed. The above method can realize the whole life cycle management of the robot and improve the management efficiency of the warehouse management system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of warehouse management, and particularly relates to a warehouse management method and system, an electronic device and a computer readable storage medium. BACKGROUND

[0002] A warehouse management system (WMS) is a management system that comprehensively uses functions such as warehouse entry business, warehouse exit business, warehouse allocation, inventory allocation and virtual warehouse management to manage functions such as batch management, material correspondence, inventory checking, quality inspection management, virtual warehouse management and real-time inventory management. In the related art, the WMS system only manages the material data stored in the warehouse, but in actual application, the materials stored in the warehouse are combined to form various products such as robots. At this time, only managing the materials in the warehouse management system is difficult to achieve end-to-end tracking management of the life cycle of the materials, which may result in inaccurate prediction and management of the materials in the warehouse and poor warehouse management. SUMMARY

[0003] The present application aims to at least solve one of the technical problems in the prior art. To this end, the present application provides a warehouse management method and system, an electronic device and a computer readable storage medium, which can improve the accuracy of prediction and management of materials in the warehouse.

[0004] In a first aspect, the present application provides a warehouse management method applied to a warehouse management system, and the method comprises the following steps.

[0005] Obtaining a robot to be predicted;

[0006] Obtaining running data of the robot from a preset operation and maintenance system, wherein the running data comprises time data and execution data;

[0007] According to the time data and the execution data, calculating the remaining life of each component to be predicted of the robot;

[0008] When the remaining life is less than a preset threshold, a life warning is performed.

[0009] According to the warehouse management method, the remaining life of each part to be predicted of the robot can be calculated according to the time data and the execution data, and the remaining life of each part to be predicted is compared with a preset threshold value, and when the remaining life is less than the preset threshold value, a life warning is given, so that the whole life cycle management of the parts from assembly to maintenance in the warehouse management system is realized through the corresponding warning, and the life cycle management of each part based on the corresponding product operation in the warehouse management system is realized, and the prediction and management precision of the materials in the warehouse is improved.

[0010] According to some embodiments of the present application, the remaining life of each part to be predicted of the robot is calculated according to the time data and the execution data, including:

[0011] The accurate running time is calculated according to the current time in the time data and the delivery time in the time data;

[0012] The running loss coefficient is calculated according to the execution data and the running time in the time data;

[0013] The remaining life is calculated according to the accurate running time and the running loss coefficient.

[0014] According to some embodiments of the present application, the execution data includes: running coefficient, robot running speed coefficient, robot load coefficient, and environmental temperature coefficient; and the running loss coefficient is calculated according to the execution data and the running time in the time data, including:

[0015] The product of the running coefficient, the robot running speed coefficient, the robot load coefficient and the environmental temperature coefficient is calculated to obtain a first coefficient product;

[0016] The product of the first coefficient product and the running time is taken as the running loss coefficient;

[0017] Correspondingly, the remaining life is calculated according to the accurate running time and the running loss coefficient, including:

[0018] The accurate running time is multiplied by the running loss coefficient to obtain a loss life;

[0019] The remaining life is obtained according to the accurate running time and the loss life.

[0020] According to some embodiments of the present application, the method further includes:

[0021] receive an ID reverse query operation instruction from a user; the ID reverse query operation instruction includes a robot ID and a query keyword;

[0022] query a plurality of first records according to the robot ID in a plurality of pre-stored first data tables;

[0023] query at least one second record according to the query keyword in at least one pre-stored second data table;

[0024] select at least one third record having the same data segment as the first record from the at least one second record;

[0025] aggregate and output the plurality of first records and the at least one third record.

[0026] According to some embodiments of the present application, the plurality of first data tables at least include one of a factory test data table and a maintenance data table; and the at least one second data table at least includes one of a commonly used spare parts list data table and a robot BOM table.

[0027] According to some embodiments of the present application, the method further includes storing the remaining life in a corresponding data table item in the commonly used spare parts list data table.

[0028] According to some embodiments of the present application, the method further includes:

[0029] obtaining part list data of the robot and preset spare part reference data;

[0030] performing multiple matches between the part list data of the robot and the spare part reference data according to a preset deep learning algorithm, to generate a commonly used spare parts list of the robot;

[0031] when there is a first spare part in the commonly used spare parts list of the robot, and the remaining life of the first spare part is less than a preset threshold, performing a restocking notification on the first spare part.

[0032] According to some embodiments of the present application, the method further includes:

[0033] obtaining part list data of the robot and preset spare part reference data;

[0034] performing multiple matches between the part list data of the robot and the spare part reference data according to a preset deep learning algorithm, to generate a commonly used spare parts list of the robot;

[0035] when there is a second spare part in the commonly used spare parts list of the robot, and the inventory quantity of the second spare part is less than a preset safety inventory, performing a restocking notification on the second spare part.

[0036] According to some embodiments of the present application, the parts list data of the robot is matched with the spare part reference data according to a preset deep learning algorithm multiple times to generate a commonly used spare part list for the robot; comprising:

[0037] The parts list data of the robot and the spare part reference data are coarsely matched according to a preset first matching rule to obtain first target data;

[0038] The first target data and the spare part reference data are finely matched according to a preset second matching rule to generate the commonly used spare part list for the robot; wherein the fields used for matching and the matching records are written into the preset spare part reference data.

[0039] According to some embodiments of the present application, a borrowing and returning operation instruction from a user is received; the borrowing and returning operation instruction comprises one of the following instructions: a material borrowing instruction, a material returning instruction, a material taking instruction and a cancellation instruction;

[0040] According to the borrowing and returning operation instruction, at least one of the following steps is performed:

[0041] According to the material borrowing instruction, the inventory data corresponding to the material number of the material to be borrowed in the material borrowing instruction is modified and a borrowing data table is generated;

[0042] According to the material returning instruction, it is judged whether the material number of the material to be returned in the material returning instruction has corresponding borrowing information to generate a returning data table;

[0043] According to the material taking instruction, the material number of the material to be taken is obtained and the inventory data of the corresponding material is modified;

[0044] According to the cancellation instruction, the material number of the material to be cancelled is obtained and the borrowing data of the corresponding borrowing data table is deleted.

[0045] According to some embodiments of the present application, the method further comprises:

[0046] A user's inventory operation instruction is received; the inventory operation instruction comprises one of the following instructions: an inventory data import instruction, an online inventory instruction and an inventory data export instruction;

[0047] According to the inventory operation instruction, at least one of the following steps is performed:

[0048] According to the inventory data import instruction, the inventory data corresponding to the inventory file imported by the user is stored after being sorted according to a preset screening rule;

[0049] According to the online inventory instruction, inventory modification data corresponding to the material information input by the user is generated;

[0050] According to the inventory data export instruction, the inventory modification data or the user uploaded inventory data is fed back.

[0051] According to some embodiments of the present application, the method further comprises;

[0052] A scheduled timing task is responded to; the scheduled timing task is one of a pre-warning timing task list;

[0053] According to the scheduled timing task, it is judged whether the timeout duration set in the scheduled timing task is timed out;

[0054] When the timeout has occurred, the operation database data corresponding to the scheduled timing task is acquired;

[0055] According to the robot data and the timeout duration, a reminder information is generated.

[0056] According to some embodiments of the present application, the pre-warning timing task list comprises: a lending and borrowing service timeout task, a material taking service un-uploaded single number timeout task, and an inventory timeout task.

[0057] In a second aspect, the present application provides a warehouse management system, which comprises the warehouse management method mentioned in any one of the first aspect, and the warehouse management system comprises:

[0058] A data aggregation module is configured to acquire running data of the robot from a preset operation and maintenance system;

[0059] A life prediction module is configured to calculate the remaining life of each predicted component of the robot according to the time data and the execution data;

[0060] A pre-warning module is configured to perform life pre-warning when the remaining life is less than a preset threshold.

[0061] The warehouse management system according to the embodiments of the present application has at least the following beneficial effects: by acquiring the time data and the execution data of the robot from the preset operation and maintenance system, the remaining life of each predicted component of the robot can be calculated according to the time data and the execution data, and the remaining life of each predicted component of the robot is compared with the preset threshold, and life pre-warning is performed when the remaining life is less than the preset threshold. Through the corresponding pre-warning, the whole life cycle management of the robot from factory to maintenance is realized, and the method is applied to the warehouse management system, so that the warehouse management system can better use the running data of the robot to realize the management of the after-sales warehouse, and improve the management efficiency.

[0062] In a third aspect, the present application provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the warehouse management method according to any one of claims 1 to 13.

[0063] According to the electronic device provided in the embodiments of the present application, at least the following beneficial effects are achieved: by obtaining the time data and execution data of the robot from the preset operation and maintenance system, and according to the time data and the execution data, the remaining life of each component to be predicted of the robot can be calculated, and the remaining life of each component to be predicted is compared with the preset threshold value, and when the remaining life is less than the preset threshold value, life warning is performed, through the corresponding warning reminder, the whole life cycle management of the robot from factory to maintenance is realized, and the method is applied to the warehouse management system, so that the warehouse management system can better use the operation data of the robot to realize the management of the after-sales warehouse, and the management efficiency is improved.

[0064] In a fourth aspect, the present application provides a computer readable storage medium, wherein the computer readable storage medium stores computer executable signals, and the computer executable signals are used to execute the warehouse management method according to claims 1 to 13.

[0065] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0066] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter.

[0067] Figure 1 A specific flowchart of the warehouse management method according to the embodiments of the present application is shown in the figure;

[0068] Figure 2 A flowchart of the warehouse management method according to another embodiment of the present application is shown in the figure;

[0069] Figure 3 An architecture diagram between the systems according to the embodiments of the present application is shown in the figure;

[0070] Figure 4 A composition diagram of the electronic device according to the embodiments of the present application is shown in the figure.

[0071] The reference signs are as follows:

[0072] Robot 100; cloud server 200; warehouse management system 300; operation and maintenance system 400; electronic device 500; memory 510; processor 520. DETAILED DESCRIPTION

[0073] Embodiments of the present application are described below in detail with reference to the accompanying drawings, examples of which are shown in the drawings, wherein the same or similar notations represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by reference to the accompanying drawings are exemplary only, and are for the purpose of explanation of the present application, and are not to be understood as limiting the present application.

[0074] In the description of the present application, it should be understood that the orientation description, such as up, down, front, back, left, right, etc., indicates the orientation or positional relationship shown in the drawings, which is only for the purpose of describing the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0075] In the description of the present application, if the first, second, etc. are described, it is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or the order of technical features indicated.

[0076] In the description of the present application, unless otherwise explicitly limited, the words such as arrangement, installation, connection, etc. should be broadly understood, and the person skilled in the art can reasonably determine the specific meaning of the above words in the present application in combination with the specific content of the technical solution.

[0077] In the related art, the WMS (Warehouse Management System) is a management system that comprehensively uses functions such as warehouse entry business, warehouse exit business, warehouse allocation, inventory allocation, and virtual warehouse management, for functions such as batch management, material correspondence, inventory checking, quality inspection management, virtual warehouse management, and real-time inventory management. However, the WMS system only manages the material data of the warehouse, and the data generated from the warehouse material to the assembly of the robot, and then to the final use of the robot cannot be well managed and applied to the analysis of the warehouse material data, and the full life cycle management of the robot is still lacking. Based on this, the present application embodiment proposes a warehouse management method.

[0078] Referring to Figure 1 and Figure 3 , in a first aspect, the present application proposes a warehouse management method applied to a warehouse management system 300, the warehouse management method includes but is not limited to the following steps:

[0079] Step S100, obtaining a robot 100 to be predicted.

[0080] It should be noted that in the warehouse management system 300, the robot 100 will be managed based on the dimension management, so as to better manage the full life cycle of the parts.

[0081] Step S200, obtaining the running data of the robot 100 from the preset operation and maintenance system 400.

[0082] It should be noted that the operation and maintenance system 400 is a system for monitoring the robot 100, which can obtain the running data of the robot 100, including power-on time, power-on time, running time, running speed, current robot temperature, current robot 100 position and other parameters.

[0083] It can be understood that the preset operation and maintenance system 400 can be a system connected with the warehouse management system 300 through the cloud server 200. The warehouse management system 300 can remotely obtain the running data of the robot 100 authorized by the user by connecting with the system.

[0084] Step S300, calculating the remaining life of each predicted component of the robot 100 according to the time data and the execution data.

[0085] It should be noted that the time data is related to the time, such as the factory time, the current time, the running time and the like. The execution data is used to represent the data of the robot 100 running condition, including environmental parameters, robot running speed coefficient, robot load coefficient and the like.

[0086] Step S400, when the remaining life is less than the preset threshold value, life warning is performed.

[0087] It should be noted that the preset threshold value is any time length value, which can also be understood as a safety threshold value. For each component in the robot 100, the safety threshold value is different. The skilled in the art does not limit the data of the preset threshold value, which can be reasonably set according to the actual safety performance evaluation; in some embodiments, the life warning information can be sent by the warehouse management system 300, and the corresponding user can be reminded by pop-up window or email.

[0088] Therefore, by obtaining the time data and the execution data of the robot 100 from the preset operation and maintenance system 400, and according to the time data and the execution data, the remaining life of each predicted component of the robot 100 can be calculated, and the remaining life of each predicted component is compared with the preset threshold value. When it is less than the preset threshold value, life warning is performed, and the corresponding warning reminds that the warehouse management system 300 can manage the life cycle of each component based on the corresponding product running condition, which can improve the prediction and management accuracy of the materials in the warehouse. The whole life cycle management of the robot 100 from factory to repair is realized, and the method is applied to the warehouse management system 300, so that the warehouse management system 300 can better use the running data of the robot 100 to realize the management of the after-sales warehouse, and improve the management efficiency.

[0089] It can be understood that step S300 includes but is not limited to the following steps:

[0090] Step S310, according to the current time in the time data and the delivery time in the time data, the accurate running time is calculated.

[0091] In some embodiments, the delivery time is the delivery time of the robot 100, which can be obtained through the preset operation and maintenance management system of the robot 100. It should be noted that the accurate running time can also be obtained through the preset operation and maintenance system 400, which can be obtained by actively monitoring the running state of the robot 100 through the operation and maintenance system 400, and finally the accurate running time of the robot 100 is calculated. The accurate running time obtained by the operation and maintenance system 400 and the accurate running time calculated by step S310 can be used as the accurate running time, and the two accurate running times can also be analyzed by error, and the data with smaller error is selected as the accurate running time.

[0092] Step S320, according to the execution data and the running time in the time data, the running loss coefficient is calculated.

[0093] Step S330, according to the accurate running time and the running loss coefficient, the remaining life is calculated.

[0094] It can be understood that the execution data includes: running coefficient, robot running speed coefficient, robot load coefficient, and environmental temperature coefficient. Correspondingly, step S320 further includes but is not limited to the following steps:

[0095] Step S321, the product of the running coefficient, the robot running speed coefficient, the robot load coefficient and the environmental temperature coefficient is calculated to obtain the first coefficient product.

[0096] In some embodiments, the calculation formula of the first product coefficient is as follows: M=K*RS*RL*AT, wherein M represents the first coefficient product, RS represents the robot running speed coefficient, RL represents the robot load coefficient, and AT represents the environmental temperature coefficient.

[0097] Step S322, the product of the first coefficient product and the running time is taken as the running loss coefficient.

[0098] In some embodiments, the calculation formula of the running loss coefficient is as follows: S=M*RT, wherein S represents the running loss coefficient, and RT represents the running time.

[0099] Correspondingly, step S330 further includes but is not limited to the following steps:

[0100] Step S331, the accurate running time is multiplied by the running loss coefficient to obtain the loss life;

[0101] Step S332, according to the precise running time and the loss life, the residual life is obtained.

[0102] Therefore, based on steps S310-S330 and steps S331, S332, the calculation formula of the residual life is as follows:

[0103]

[0104] Wherein, BT represents the residual life, (CT-DT)*HT represents the precise running time, HT represents the conversion hours,

[0105] (CT-DT)*RT*M represents the loss life, by subtracting the residual life from the loss life, the part life of each component of the robot to be predicted is obtained.

[0106] It can be understood that, with reference to Figure 2 The warehouse management method further includes but is not limited to the following steps:

[0107] Step S510, receiving an ID reverse query operation instruction from a user; the ID reverse query operation instruction includes a robot ID and a query keyword.

[0108] It should be noted that the information of the robot 100 can be obtained more accurately through the query keyword and the robot ID (serial number).

[0109] Step S520, according to the robot ID, a plurality of first records are obtained by querying in a plurality of pre-stored first data tables.

[0110] Step S530, according to the query keyword, at least one second record is obtained by querying in at least one pre-stored second data table.

[0111] It can be understood that the plurality of first data tables at least include one of the factory test data table and the maintenance data table, and the at least one second data table at least includes one of the commonly used spare parts list data table and the robot BOM table.

[0112] Exemplarily, the robot BOM table contains data items such as material number, specification, quantity, storage position, batch, storage position, remarks; the factory test data table contains data items such as robot serial number (ID), robot repeated positioning accuracy data, electrical measurement data, CT test data, reducer parameters, assembly time, assembly personnel, assembly location, robot picture, etc.; the maintenance data table contains data items such as robot serial number, standard life of parts and components, service life of parts and components, replacement time of parts and components, replacement personnel, replacement location, etc.; the commonly used spare parts list data table contains data items such as the commonly used spare parts list of the current robot 100, including electrical, mechanical and software.

[0113] Step S540, selecting at least one third record having the same data segment as the first record in at least one second record.

[0114] It can be understood that through the ID reverse query operation instruction of the robot 100 in response to the ID+ query keyword, the data linkage between multiple tables can be realized according to the filtering method mentioned in step S540. For example, through the ID+1-axis motor reducer assembly, the standard life of the 1-axis motor reducer assembly under the ID of the current robot can be queried, the current use time, the current replacement and maintenance condition, the current warehouse, the spare part condition in the warehouse, and the factory test condition, etc. Therefore, through the ID reverse query operation instruction, the future maintenance condition of the robot 100 can be analyzed according to the reverse query result, and the full life cycle data report of the robot 100 can be provided for the customer and the enterprise.

[0115] Step S550, aggregating and outputting the plurality of first records and the at least one third record.

[0116] It can be understood that the warehouse management system 300 can use SQL statements to perform global multi-table query on the plurality of first data tables and the at least one second data table through the ID of the robot and the query keyword provided by the user, aggregate all data of this ID, and return to the front-end user through specific analysis and filtering, so as to realize the data linkage between multiple data tables, query the relevant data of the ID of the robot 100 and the keyword input by the user through less information, and realize global query of multiple tables.

[0117] It can be understood that the warehouse management method further includes but is not limited to the following steps:

[0118] Step S610, storing the remaining life in the corresponding data table item of the frequently-used spare parts list data table.

[0119] It can be understood that by storing the remaining life in the corresponding data table item of the frequently-used spare parts list data table, data support can be provided for subsequent warehouse management system 300 for inventory analysis of specific spare parts list. At the same time, through the ID reverse query operation instruction, the production, operation, maintenance, and remaining life of parts of the robot 100 can be reverse queried, the future maintenance condition of the robot 100 can be analyzed according to the reverse query result, and the full life cycle data report of the robot 100 can be provided for the customer and the enterprise.

[0120] It can be understood that the warehouse management method further includes but is not limited to the following steps:

[0121] Step S620, obtaining the part list data of the robot 100 and the preset spare part reference data.

[0122] It should be noted that the parts list data of the robot 100 can be obtained through the preset operation and maintenance system 400, and the preset spare part reference data can be a commonly used spare part list obtained through internal big data analysis of the warehouse management system 300, which is an original reference data for subsequent matching.

[0123] In step S630, the parts list data of the robot 100 is matched with the spare part reference data according to the preset deep learning algorithm, and the commonly used spare part list of the robot 100 is generated.

[0124] It can be understood that by matching the parts list data of the robot 100 with the spare part reference data multiple times, the data items in the parts list data of the robot 100 that meet the reference standard provided by the spare part reference data are output, and the commonly used spare part list data corresponding to the robot 100 of a specific ID is generated. Therefore, it can be understood that the commonly used spare parts and spare parts of the robot 100 of a specific ID are needed, which facilitates subsequent targeted restocking or reduces the inventory quantity of spare parts and spare parts list with low demand.

[0125] In step S640, when the remaining life of the first component in the commonly used spare part list of the robot 100 is less than the preset threshold, the first component is notified of the restocking.

[0126] It can be understood that by screening the first component with a remaining life less than the preset threshold value in the commonly used spare part list of the robot 100, and notifying the first component of the restocking, the warehouse manager can clearly understand the maintenance condition of the robot 100 sold, and can restock the spare parts and spare parts needed, thereby improving the efficiency of warehouse management.

[0127] It can be understood that the triggering condition of the restocking notification in step S640 also includes but is not limited to the following steps:

[0128] In step S641, when the inventory quantity of the second component in the commonly used spare part list of the robot 100 is less than the preset safety stock, the second component is notified of the restocking.

[0129] It can be understood that the commonly used spare part list of the robot 100 is extracted from the parts list data of the current robot 100 by the deep learning algorithm, and the inventory quantity of the commonly used spare part is compared with the safety stock quantity. If the inventory quantity of the commonly used spare part exceeds the safety stock, no restocking notification is needed. When the inventory quantity of the commonly used spare part is less than the safety stock, the restocking notification of the corresponding component is performed, thereby realizing the reasonable allocation of the inventory in the warehouse management and improving the efficiency of the inventory management.

[0130] It should be noted that the trigger conditions of the spare parts notification in steps S640 and S641 can be complementary, and in some embodiments, both trigger conditions can be applied to the warehouse management method, that is, the warehouse management system 300 detects the remaining life and the inventory quantity of each spare part in the commonly used spare parts list of the current robot 100, and as long as any one of the trigger conditions in steps S640 or S641 is met, the spare parts notification of the corresponding spare part can be realized. In some embodiments, the quantity of spare parts that need to be replenished can also be calculated according to the weight of the remaining life of the spare parts in the commonly used spare parts list of the current robot 100 and the corresponding inventory quantity, thereby enhancing the management efficiency of the inventory capacity.

[0131] It can be understood that step S630 further includes but is not limited to the following steps:

[0132] Step S631, according to a preset first matching rule, performing coarse matching on the part list data of the robot 100 and the spare part reference data to obtain first target data;

[0133] It can be understood that the first matching rule is a matching method predefined by the warehouse management system 300, and the present application does not make specific limitations on the first matching rule. According to the part list data of the robot 100, the spare part reference data in the stored database is first roughly screened, and a large range of target data is extracted. Coarse matching mainly quickly screens out unnecessary data, preferentially reduces the data quantity, and improves the matching efficiency.

[0134] Step S632, according to a preset second matching rule, performing fine matching on the first target data and the spare part reference data to generate a commonly used spare parts list of the robot.

[0135] It can be understood that after coarse matching, most of the unnecessary data has been screened out. At this time, according to the preset second matching rule, fine matching is performed to ensure the accuracy of the matching. At this time, the data quantity is small, and the time consumption is also less. Coarse matching and fine matching are combined to match the commonly used spare parts list corresponding to the current robot 100 from the part list data of the robot 100, and the matching accuracy is high while the efficiency is also high.

[0136] It can be understood that the fields used for matching and the matching records will be written into the preset spare part reference data. By writing the extracted records and data fields into the preset spare part reference data, the data quantity of the matching database can be expanded to improve the matching accuracy.

[0137] It can be understood that the warehouse management method further includes but is not limited to the following steps:

[0138] Step S710, receiving a borrowing and returning operation instruction from a user.

[0139] According to the borrowing and returning operation instruction, at least one of the following steps is performed:

[0140] In step S720, according to the material borrowing instruction, the inventory data corresponding to the material number of the material to be borrowed in the material borrowing instruction is modified, and a borrowing data table is generated.

[0141] In step S730, according to the material returning instruction, it is judged whether the material number of the material to be returned in the material returning instruction has corresponding borrowing information, so as to generate a returning data table.

[0142] In step S740, according to the material taking instruction, the material number of the material to be taken is obtained, and the inventory data of the corresponding material is modified.

[0143] In step S750, according to the account closing instruction, the material number of the material to be closed is obtained, and the borrowing data of the corresponding borrowing data table is deleted.

[0144] For the material borrowing instruction: the warehouse management system 300 returns the specifications, quantities, positions, etc. according to the user input content using the Ajax local update method. At this time, the user submits the form, the background flask route obtains the form information, uses the self-compiled class to process the user's borrowing data, modifies the data of the inventory and the borrowing and returning table, and adds backup records to the borrowing and returning table.

[0145] Material returning instruction: by obtaining the user input material number, the system uses Ajax technology to judge whether there is current user borrowing information. If there is, return the borrowing information for returning. If there is no borrowing information, it cannot be returned. The returning logic is similar to the borrowing logic, except that the data table operated is different.

[0146] For the material taking instruction: when the user determines that the material is borrowed and not returned, through the material taking instruction, its logic is consistent with the material borrowing instruction, and the only difference is that the material taking instruction does not operate the borrowing and returning data table.

[0147] According to the account closing instruction: when the user borrowed material is changed to taking, at this time, through the account closing instruction, the borrowing information can be deleted, and the data of the inventory is updated.

[0148] Therefore, through the steps of responding to the above borrowing and returning operation instructions, the warehouse management system 300 not only has basic inventory management, but also further enriches the functions of the system. Compared with the traditional warehouse management system 300 for material out-of-stock and material in-stock management, the management of the whereabouts of the material is more detailed, the whereabouts of the material is more clear and transparent, and the function of the warehouse management is more perfect.

[0149] It can be understood that the warehouse management method further includes but is not limited to the following steps:

[0150] Step S810, receiving the inventory operation instruction from the user.

[0151] According to the inventory operation instruction, at least one of the following steps is performed:

[0152] Step S820, according to the inventory data import instruction, the inventory data corresponding to the inventory file imported by the user is stored after being sorted according to the preset filtering rule.

[0153] Step S830, according to the online inventory instruction, the inventory modification data corresponding to the material information entered by the user is generated.

[0154] Step S840, according to the inventory data export instruction, the inventory modification data or the inventory data uploaded by the user is fed back.

[0155] It can be understood that for the inventory data import instruction, the warehouse management system 300 uploads the data to be inventoried (inventory file) through the file upload function of HTML. The backend of the warehouse management system 300 obtains and saves the file to the server through the route of flask, and transmits the self-compiled class filtering data into the system database according to the file saving address, so as to realize the import of offline inventory data into the warehouse management system 300, thereby compatible with the offline operation of warehouse management, so that the offline inventory operation can be relatively simple when it is transferred to online inventory, without the need to repeat the inventory, and the past inventory data is also effective.

[0156] For the online inventory instruction, the warehouse management system 300 obtains the content entered by the user or the content entered by the code scanning gun. The content can be the material number or other data representing the material information. The specification, inventory quantity, and the like are returned by using the Ajax local update mode. At this time, the user only needs to check the actual inventory quantity, click the submit form, and the flask route in the background obtains the form information and uses SQL to modify the inventory data, thereby achieving the effect of online inventory.

[0157] For the inventory data export instruction, the warehouse system reads the inventory data of the database by SQL and saves it to the specified server path by using Pandas. The path is fed back to the front-end user. By using the browser feature, the user can directly download the data file under the corresponding path, thereby achieving the purpose of data export. It should be noted that the inventory data of the database can be the inventory data imported from offline before, or the data generated by the user during online inventory. By adapting the export and import of multiple types of inventory data, when the offline inventory is changed to online inventory or the offline inventory is changed to online inventory, the inventory data is always universal, which is more convenient for the user.

[0158] It can be understood that the warehouse management method further comprises:

[0159] Step S910, responding to the scheduling timing task;

[0160] In step S920, it is judged whether the timeout time length set in the scheduled timing task is timed out according to the scheduled timing task.

[0161] In step S930, when the timeout time length is timed out, the operation database data corresponding to the scheduled timing task is acquired.

[0162] It should be noted that the data of the operation database is different for different timing tasks. For example, if the scheduled timing task is to check whether the borrowed material operation is returned within the specified time, the operation database data acquired will be the borrowing registration table or the returning registration table. Therefore, the content of the operation database is not limited in the present application, and a person skilled in the art can reasonably set the read operation database data according to the type of the timing task.

[0163] In step S940, the reminding information is generated according to the robot data and the timeout time length.

[0164] It can be understood that the early warning timing task list includes a borrowing and returning service timeout task, a material taking service single number uploading timeout task, and an inventorying timeout task.

[0165] It should be noted that the warehouse management system 300 automatically executes different timing tasks by scheduling the timing tasks. When the execution condition is met, the corresponding database data is read, the current set timing task is combined for data analysis, and the corresponding user is automatically reminded by email according to the analysis result. In some embodiments, the analysis result is also saved for backup. For example, for the borrowing and returning task of the user in the warehouse management system 300, the warehouse management system 300 reads the borrowing and returning data table regularly. If the returning data table or the borrowing data table of the corresponding material is not detected within the preset timeout time length, it indicates that the material is not returned or borrowed in time. The system will send an email to the borrower's mailbox to remind the user to return or borrow the material in time. In addition, when the user operates the material taking task in the warehouse management system 300, if the single number uploaded by the user is not found in the warehouse management system 300, an email or other reminding method will be sent to remind the user to upload the single number in time. By setting the timing reminding task, the normal and stable operation of the warehouse management system 300 can be ensured.

[0166] In a second aspect, the present application further provides a warehouse management system 300, which comprises the warehouse management method of the first method embodiment. The warehouse management system 300 comprises:

[0167] The data aggregation module is configured to acquire the running data of the robot 100 in the preset operation and maintenance system 400.

[0168] a life prediction module configured to calculate the remaining life of each component of the robot 100 to be predicted according to the time data and the execution data.

[0169] a pre-warning module configured to perform life pre-warning when the remaining life is less than a preset threshold.

[0170] In some embodiments, the pre-warning module is further configured to perform timeout pre-warning on functions such as material borrowing, returning, order number uploading after material taking, and material inventory in the warehouse management system 300. Through a set timing task, it is periodically detected whether there is a task timeout, and the corresponding personnel is reminded through a contact method such as email and short message.

[0171] It can be understood that the warehouse management system 300 of the present application is a front-end and back-end separated web page interactive system based on Python developed on the basis of an after-sales warehouse, which improves the warehouse management efficiency and ensures the inventory accuracy, and realizes traceability of historical records from offline to online.

[0172] Therefore, by obtaining the time data and the execution data of the robot 100 from the preset operation and maintenance system 400, and according to the time data and the execution data, the remaining life of each component of the robot 100 to be predicted can be calculated, and the remaining life of each component to be predicted is compared with the preset threshold. When it is less than the preset threshold, life pre-warning is performed, the whole life cycle management of the robot 100 from factory to maintenance is realized through corresponding pre-warning, and the method is applied to the warehouse management system 300, so that the warehouse management system 300 can better use the operation data of the robot 100 to realize the management of the after-sales warehouse, and improve the management efficiency.

[0173] In a third aspect, referring to Figure 4 The present application also provides an electronic device 500 comprising a memory 510 and a processor 520, and the warehouse management method provided in the first aspect is stored in the memory 510 and read and executed by the processor 520 to perform the steps of the above method, wherein the memory 510 and the processor 520 complete data transmission and communication through a bus.

[0174] The memory 510 is a non-transitory computer readable storage medium, which can be used to store non-transitory software programs, non-transitory computer executable programs and signals, such as program instructions / signals corresponding to the electronic control module in the embodiment of the present application. The processor 520 performs various functional applications and data processing by running the non-transitory software programs, instructions and signals stored in the memory 510, that is, implements the warehouse management method of the above method embodiment.

[0175] The memory 510 can include a program storage area and a data storage area, where the program storage area can store an operating system, at least one application required by the function, and the data storage area can store relevant data of the above-mentioned warehouse management method, etc. In addition, the memory 510 can include a high-speed random access memory 510, and can also include a non-transitory memory 510, such as at least one disk memory 510, a flash memory device, or other non-transitory solid-state memory 510. In some embodiments, the memory 510 can optionally include a memory 510 that is remotely arranged with respect to the processor 520, and these remote memories 510 can be connected to the processing module through a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0176] One or more signals are stored in the memory 510, and when executed by the one or more processors 520, the warehouse management method in any of the above-mentioned method embodiments is executed. For example, the methods of steps S100-S400, steps S310-S330, steps S321-S322, steps S331-S332, steps S510-S550, steps S610-S640, step S641, steps S631-S632, steps S710-S750, steps S810-S840, steps S910-S940 are executed.

[0177] In a fourth aspect, the embodiments of the present application provide a computer readable storage medium, and the computer readable storage medium stores computer executable instructions, and the computer executable instructions are executed by the one or more processors 520, and can make the above-mentioned one or more processors 520 execute the warehouse management method in the above-mentioned method embodiments. For example, the methods of steps S100-S400, steps S310-S330, steps S321-S322, steps S331-S332, steps S510-S550, steps S610-S640, step S641, steps S631-S632, steps S710-S750, steps S810-S840, steps S910-S940 are executed.

[0178] Those of ordinary skill in the art will appreciate that all or certain steps, systems of the methods disclosed above can be implemented as software, firmware, hardware, and appropriate combinations thereof. Certain physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software can be distributed on computer readable media, which can include computer storage media (or non-transitory media) and communication media (or transitory media). As is well known to those of ordinary skill in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Further, it is common knowledge to those of ordinary skill in the art that communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.

[0179] The device embodiments described above are merely illustrative, wherein the units illustrated as separate components can or can not be physically separate, and the components illustrated as units can or can not be physical units, i.e., can be located in one place, or can be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purposes of the embodiments.

[0180] The embodiments of the present application are described in detail above in combination with the drawings, but the present application is not limited to the above embodiments, and various changes can be made within the knowledge of those of ordinary skill in the art without departing from the purpose of the present application.

Claims

1. A warehouse management method, characterized in that, Applied to a warehouse management system, the method includes: Obtain the robot to be predicted; The robot's operational data is obtained from a pre-set operation and maintenance system; the operational data includes time data and execution data. Based on the time data and the execution data, calculate the remaining lifespan of each component of the robot to be predicted; When the remaining lifespan is less than a preset threshold, a lifespan warning is issued; The remaining lifespan is stored in the corresponding data entry of the commonly used spare parts list data table; The execution data includes: operating coefficient, robot operating speed coefficient, robot load coefficient, and ambient temperature coefficient; the calculation of the remaining lifespan of each component of the robot to be predicted based on the time data and the execution data includes: The precise running time is calculated based on the current time and the shipping time in the time data. Calculate the product of the operating coefficient, the robot operating speed coefficient, the robot load coefficient, and the ambient temperature coefficient to obtain the first coefficient product; The product of the first coefficient and the running time is used as the running loss coefficient. The remaining lifespan is calculated based on the precise operating time and the operating loss coefficient. The method further includes: Receives a reverse ID query instruction from a user; the reverse ID query instruction includes the robot ID and query keywords. Multiple first records are obtained by querying the robot ID in multiple pre-stored first data tables; In at least one pre-stored second data table, at least one second record is obtained by querying according to the query keyword; the at least one second data table includes a commonly used spare parts list data table; Select at least one third record from the at least one second record that has the same data segment as the first record; Summarize and output multiple first records and at least one third record.

2. The warehouse management method according to claim 1, characterized in that, The calculation of the remaining lifespan based on the precise operating time and the operating loss coefficient includes: Multiply the precise running time by the running loss coefficient to obtain the wear life; The remaining lifespan is obtained based on the precise operating time and the wear-out lifespan.

3. The warehouse management method according to claim 2, characterized in that, The plurality of first data tables include at least one of the factory test data table and the maintenance data table; the at least one second data table also includes the robot BOM table.

4. The warehouse management method according to claim 1, characterized in that, The method further includes: Obtain the parts list data of the robot and the preset spare parts reference data; The robot's parts list data is matched with spare parts reference data multiple times using a preset deep learning algorithm to generate a list of commonly used spare parts for the robot. If the robot's commonly used spare parts list contains a first component whose remaining lifespan is less than a preset threshold, a stock replenishment notice will be issued for the first component.

5. The warehouse management method according to claim 1, characterized in that, The method further includes: Obtain the parts list data of the robot and the preset spare parts reference data; The robot's parts list data is matched with spare parts reference data multiple times using a preset deep learning algorithm to generate a list of commonly used spare parts for the robot. If the inventory quantity of a second component in the robot's commonly used spare parts list is less than the preset safety stock, a notification will be sent to prepare the second component.

6. The warehouse management method according to claim 4 or 5, characterized in that, The step of generating a list of commonly used spare parts for the robot by repeatedly matching the robot's parts list data with spare parts reference data according to a preset deep learning algorithm includes: According to the preset first matching rule, the parts list data of the robot and the spare parts reference data are coarsely matched to obtain the first target data; According to the preset second matching rule, the first target data is finely matched with the spare parts reference data to generate the list of commonly used spare parts for the robot.

7. The warehouse management method according to claim 1, characterized in that, The method further includes: Receive borrowing and returning operation instructions from users; the borrowing and returning operation instructions include one of the following instructions: material borrowing instruction, material return instruction, material requisition instruction, and account cancellation instruction; Perform at least one of the following steps according to the borrowing / returning operation instructions: Based on the material borrowing instruction, modify the inventory data corresponding to the material number of the material to be borrowed in the material borrowing instruction and generate a borrowing data table; Based on the material return instruction, determine whether the material number to be returned in the material return instruction has corresponding borrowing information, so as to generate a return data table; Based on the material requisition instruction, obtain the part number of the material to be requisitioned and modify the corresponding material's inventory data; According to the write-off instruction, obtain the material number of the material to be written off, and delete the corresponding borrowing data in the borrowing data table.

8. The warehouse management method according to claim 1, characterized in that, The method further includes: Receive inventory operation instructions from users; the inventory operation instructions include one of the following: inventory data import instruction, online inventory instruction, and inventory data export instruction. Perform at least one of the following steps according to the inventory operation instructions: According to the inventory data import instruction, the inventory data corresponding to the user-imported inventory file is sorted and stored using preset filtering rules; Based on the online inventory instructions, generate inventory modification data corresponding to the material information entered by the user; Based on the inventory data export command, the modified inventory data or the inventory data uploaded by the user is fed back.

9. The warehouse management method according to claim 8, characterized in that, The method further includes; The response is a scheduled task; the scheduled task is one of the early warning scheduled tasks in the list. Based on the scheduled task, determine whether the timeout duration set in the scheduled task has expired; When the timeout has occurred, retrieve the operation database data corresponding to the scheduled task; Based on the database data and timeout duration, a reminder message is generated.

10. The warehouse management method according to claim 9, characterized in that, The list of timed early warning tasks includes: borrowing and returning service timeout task, material collection service timeout task for not uploading order number, and inventory timeout task.

11. A warehouse management system, characterized in that, The system comprising the warehouse management method according to any one of claims 1 to 10, wherein the system includes: The data aggregation module is used to acquire the operating data of the robot in the preset operation and maintenance system; The lifespan prediction module is used to calculate the remaining lifespan of each component of the robot to be predicted based on the time data and the execution data; and to store the remaining lifespan in the corresponding data table entry of the commonly used spare parts list data table. The early warning module is used to issue a lifespan warning when the remaining lifespan is less than a preset threshold value; The execution data includes: operating coefficient, robot operating speed coefficient, robot load coefficient, and ambient temperature coefficient; the calculation of the remaining lifespan of each component of the robot to be predicted based on the time data and the execution data includes: The precise running time is calculated based on the current time and the shipping time in the time data. Calculate the product of the operating coefficient, the robot operating speed coefficient, the robot load coefficient, and the ambient temperature coefficient to obtain the first coefficient product; The product of the first coefficient and the running time is used as the running loss coefficient. The remaining lifespan is calculated based on the precise operating time and the operating loss coefficient. The warehouse management system is also configured to receive ID reverse query operation instructions from users; the ID reverse query operation instructions include robot ID and query keywords; in multiple pre-stored first data tables, multiple first records are retrieved based on the robot ID; in at least one pre-stored second data table, at least one second record is retrieved based on the query keywords; the at least one second data table includes a commonly used spare parts list data table; at least one third record with the same data segment as the first record is selected from the at least one second record; the multiple first records and at least one third record are summarized and output.

12. An electronic device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the warehouse management method according to any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable signals for performing the warehouse management method as described in any one of claims 1 to 10.

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