CN114792222B - Supervision method, system and device applied to wholesale of electronic products - Google Patents
Supervision method, system and device applied to wholesale of electronic products Download PDFInfo
- Publication number
- CN114792222B CN114792222B CN202210714390.3A CN202210714390A CN114792222B CN 114792222 B CN114792222 B CN 114792222B CN 202210714390 A CN202210714390 A CN 202210714390A CN 114792222 B CN114792222 B CN 114792222B
- Authority
- CN
- China
- Prior art keywords
- product
- transaction
- electronic
- warehousing
- electronic products
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000012544 monitoring process Methods 0.000 claims abstract description 40
- 230000000694 effects Effects 0.000 claims abstract description 29
- 238000000605 extraction Methods 0.000 claims description 62
- 238000004364 calculation method Methods 0.000 claims description 51
- 238000012545 processing Methods 0.000 claims description 20
- 230000003203 everyday effect Effects 0.000 claims description 17
- 238000004590 computer program Methods 0.000 claims description 5
- 238000004891 communication Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 230000007547 defect Effects 0.000 description 2
- 239000004973 liquid crystal related substance Substances 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000000802 evaporation-induced self-assembly Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
- G06Q10/0875—Itemisation or classification of parts, supplies or services, e.g. bill of materials
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0623—Item investigation
- G06Q30/0625—Directed, with specific intent or strategy
- G06Q30/0629—Directed, with specific intent or strategy for generating comparisons
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Business, Economics & Management (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- General Business, Economics & Management (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- Development Economics (AREA)
- Theoretical Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Human Resources & Organizations (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a supervision method, a system and a device applied to wholesale of electronic products; belongs to the technical field of wholesale of electronic products; the electronic products in different states at different stages in the wholesale process are screened out through omnibearing monitoring and analysis on warehousing, loading and trading of the electronic products in different types, and the wholesale conditions of the electronic products in different stages are analyzed and evaluated through the simultaneous connection of the electronic products in different states, so that the optimal money and the worst money of the electronic products can be screened out, and the optimal money can be kept in high-efficiency ordered goods feeding and the bad money and loading are carried out so as to introduce new money, and the wholesale supervision effect of the electronic products is effectively improved; the invention is used for solving the technical problem that the wholesale supervision effect of the electronic product is poor because the wholesale of different types of electronic products cannot be monitored and analyzed in an all-round manner in the existing scheme.
Description
Technical Field
The invention relates to the technical field of electronic product wholesale, in particular to a supervision method, a supervision system and a supervision device applied to electronic product wholesale.
Background
Electronic products are related products based on electric energy.
When the existing supervision scheme applied to electronic product wholesale is implemented, the electronic product is put on shelf and restocked only based on the stock and trade conditions of the electronic product, and the whole flow of warehousing, putting on shelf and trade wholesale of different types of electronic products cannot be dynamically monitored and early-warning prompted in a self-adaptive manner, so that the monitoring effect of the wholesale of the different types of electronic products is poor.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a supervision method, a system and a device applied to electronic product wholesale, which are used for solving the technical problem that the supervision effect of electronic product wholesale is poor because the wholesale of different types of electronic products cannot be monitored and analyzed in an all-round manner in the prior art.
The aim of the invention can be achieved by the following technical scheme:
the supervision method applied to electronic product wholesale comprises the following steps:
monitoring and counting the warehousing conditions of the electronic products every day to obtain a warehousing set of the electronic products; performing numerical processing on each item of data in the warehouse-in set to obtain a first extraction set; the warehousing set comprises the product types, the warehousing quantity and the warehousing time of the electronic products;
Monitoring and counting the on-shelf conditions of the electronic products every day to obtain an on-shelf set of the electronic products; performing numerical processing on each item of data in the upper rack set to obtain a second extraction set; the shelf set comprises a shelf region, shelf time and browsing amount of the electronic product;
monitoring and counting the trade conditions of the electronic products every day to obtain a trade set of the electronic products; performing numerical processing on each item of data in the transaction set to obtain a third extraction set;
the transaction set comprises the number of orders in the electronic product, the number of products in the transaction, the number of non-orders in the transaction and the number of non-products in the transaction;
respectively calculating and analyzing the first extraction set, the second extraction set and the third extraction set to obtain a first calculation set containing warehouse-in coefficients, a second calculation set containing shelf coefficients and a third calculation set containing warehouse-out coefficients; the first computing set, the second computing set and the third computing set form a monitoring total set;
and analyzing and prompting wholesale conditions of different types of electronic products according to the monitoring collection.
Further, the specific step of obtaining the first extraction set includes:
obtaining the product types, the warehousing quantity and the warehousing time of the centralized electronic products;
matching the product type with a pre-constructed product association table to obtain a corresponding product association value and marking the product association value as CG; the product association table consists of different types of electronic products and corresponding product association values thereof, wherein the different types of electronic products are preset with a corresponding product association value;
Extracting numerical values in the warehouse-in quantity and marking the numerical values as RS; setting the warehousing time of the electronic product as a first timestamp;
the marked product association value, the warehouse-in quantity and the first timestamp form a first extraction set;
calculating each item of data marked in the first extraction set through a formula to obtain a warehousing coefficient RKX of the electronic product; the formula is rkx=cg RS;
analyzing the warehouse-in coefficients to obtain a warehouse-in analysis set; the binning coefficients and binning analysis set form a first calculation set.
Further, the specific steps of obtaining the warehouse entry analysis set include:
obtaining a corresponding product judgment threshold according to the product type, and matching the warehouse-in coefficient with the product judgment threshold;
if the warehousing coefficient is not greater than m% of the product judgment threshold value, judging that the electronic product inventory of the type is insufficient and generating a first warehousing signal; m is a real number greater than zero; setting the electronic products of the type as first warehouse-in products according to the first warehouse-in signals;
if the warehousing coefficient is greater than m% of the product judgment threshold value and is not greater than (200-m)% of the product judgment threshold value, judging that the electronic product inventory of the type is normal and generating a second warehousing signal;
if the warehousing coefficient is greater than (200-m)% of the product judgment threshold value, judging that the type of electronic product is excessive in inventory and generating a third warehousing signal; setting the electronic product of the type as a second warehouse-in product according to the third warehouse-in signal;
The first warehousing product, the second warehousing product, the first warehousing signal, the second warehousing signal and the third warehousing signal form a warehousing analysis set.
Further, the specific step of obtaining the second extraction set includes:
acquiring a racking area, racking time and browsing amount of electronic products in a racking set;
setting different upper frame areas to correspond to different area weights, matching the upper frame areas in the upper frame set with all the upper frame areas to obtain corresponding area weights, and marking the corresponding area weights as QQ;
extracting the numerical value of the browsing amount and marking the numerical value as LL; setting the time to be on shelf as a second timestamp; acquiring the time difference between the second time stamp and the first time stamp and setting the time difference as a first time difference YS;
the marked area weight, browsing amount, second time stamp and first time difference form a second extraction set;
calculating each item of data marked in the second extraction set through a formula to obtain a shelf-up coefficient SJX of the electronic product; the formula is sjx=qq (a 1 LL-a2 ys+ 0.2537); a1 and a2 are different scaling factors and are both greater than zero;
analyzing the racking coefficient to obtain a racking analysis set; the racking coefficients and the racking analysis set form a second calculation set.
Further, the specific steps of obtaining the set of on-shelf analysis include:
Obtaining a corresponding shelving judging range according to the product type, and matching the shelving coefficient with the shelving judging range;
if the shelving coefficient is smaller than the minimum value of the shelving judging range, judging that the display effect of the shelving electronic product is poor and generating a first shelving signal; setting the corresponding electronic product as a first shelf product according to the first shelf signal;
if the shelving coefficient is not smaller than the minimum value of the shelving determination range and not larger than the maximum value of the shelving determination range, judging that the display effect of the shelving electronic product is normal and generating a second shelving signal;
if the shelving coefficient is larger than the maximum value of the shelving judging range, judging that the display effect of the shelving electronic product is good and generating a third shelving signal; setting the corresponding electronic product as a second shelf product according to the third shelf signal;
the first overhead product, the second overhead product, the first overhead signal, the second overhead signal, and the third overhead signal comprise an overhead analysis set.
Further, the specific step of obtaining the third extraction set includes:
acquiring the number of orders, the number of products, the number of non-orders and the number of non-products of the electronic products in the transaction set;
respectively extracting the numerical values of the number of orders and the number of products to be delivered and marking the numerical values as CC and CS;
Respectively extracting the numerical values of the number of the undeveloped orders and the number of the undeveloped products and marking the numerical values as DD and DC;
the marked amount of orders, the number of products to be delivered, the number of non-orders to be delivered and the number of non-products to be delivered form a third extraction set;
calculating each item of data marked in the third extraction set through a formula to obtain a transaction coefficient JYX of the electronic product; the formula is JYX=b1+CC/(DD+ 0.3652) +b2+CS/(DC+ 0.8537); b1 and b2 are different scaling factors and are both greater than zero;
analyzing the transaction coefficients to obtain a transaction analysis set; the transaction coefficients and the transaction analysis set form a third calculation set.
Further, the specific steps of obtaining the transaction analysis set include:
obtaining a corresponding transaction judging range according to the product type, and matching the transaction coefficient with the transaction judging range;
if the transaction coefficient is smaller than the minimum value of the transaction judging range, judging that the transaction result of the electronic product is poor and generating a first transaction signal; setting the electronic product corresponding to the product type as a first transaction product according to the first warehouse-in signal;
if the transaction coefficient is not smaller than the minimum value of the transaction judging range and not larger than the maximum value of the transaction judging range, judging that the transaction result of the electronic product is normal and generating a second transaction signal;
If the transaction coefficient is greater than the maximum value of the transaction judging range, judging that the transaction result of the electronic product is excellent and generating a third transaction signal; setting the electronic product corresponding to the product type as a second transaction product according to the third warehousing signal;
the first transaction product, the second transaction product, the first transaction signal, the second transaction signal, and the third transaction signal comprise a transaction analysis set.
Further, the specific steps of analyzing and prompting wholesale conditions of different types of electronic products according to the monitoring collection comprise:
acquiring a first calculation set, a second calculation set and a third calculation set in a monitoring total set;
matching the first warehouse-in product and the second warehouse-in product contained in the first calculation set, the first shelf-up product and the second shelf-up product contained in the second calculation set, and the first transaction product and the second transaction product contained in the third calculation set;
if the second warehouse-in product, the first shelf-up product and the first transaction product are the same electronic product, judging that the wholesale effect of the electronic product is poor and generating a shelf-down signal; adding one to the next number of the electronic product according to the next signal; counting the total number of the electronic products in the period of one week, arranging the electronic products in descending order, and setting the first electronic product as the lower frame product;
If the first warehouse-in product, the second shelf-up product and the second transaction product are the same electronic product, judging that the wholesale effect of the electronic product is good and generating a replenishment signal; adding one to the replenishment times of the electronic product according to the replenishment signal; counting the total number of replenishment of all electronic products in a week, arranging the electronic products in a descending order, and setting the first electronic product as a replenishment product;
the shelf-down signal and the replenishment signal as well as the shelf-down product and the replenishment product form an analysis set of electronic product wholesale, and corresponding early warning and prompt are sent to an administrator according to different signals in the analysis set, so that the administrator can timely carry out product shelf-down and product replenishment.
In order to solve the problems, the invention also provides a supervision system applied to wholesale of electronic products, which comprises a warehousing module, an on-shelf module, a transaction module, a calculation module and a management module;
the warehousing module is used for monitoring and counting the warehousing conditions of the electronic products every day to obtain a warehousing set of the electronic products; performing numerical processing on each item of data in the warehouse-in set to obtain a first extraction set; the warehousing set comprises the product types, the warehousing quantity and the warehousing time of the electronic products;
the shelving module is used for monitoring and counting the shelving situation of the electronic products every day to obtain a shelving set of the electronic products; performing numerical processing on each item of data in the upper rack set to obtain a second extraction set; the shelf set comprises a shelf region, shelf time and browsing amount of the electronic product;
The transaction module is used for monitoring and counting the transaction condition of the electronic products every day to obtain a transaction set of the electronic products; performing numerical processing on each item of data in the transaction set to obtain a third extraction set; the transaction set comprises the number of orders in the electronic product, the number of products in the transaction, the number of non-orders in the transaction and the number of non-products in the transaction;
the calculation module is used for respectively calculating and analyzing the first extraction set, the second extraction set and the third extraction set to obtain a first calculation set containing the warehouse-in coefficients, a second calculation set containing the put-on coefficients and a third calculation set containing the warehouse-out coefficients; the first computing set, the second computing set and the third computing set form a monitoring total set;
and the management module is used for analyzing and prompting wholesale conditions of different types of electronic products according to the monitoring collection.
In order to solve the above problems, the present invention also provides a supervision device applied to wholesale of electronic products, which is characterized by comprising at least one processor;
and a memory communicatively coupled to the at least one processor; the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor, so that the at least one processor can execute the supervision method applied to wholesale of the electronic product.
Compared with the prior art, the invention has the beneficial effects that:
the electronic products in different states at different stages in the wholesale process are screened out through comprehensive monitoring and analysis on warehousing, loading and trading of the electronic products in different types, the wholesale conditions of the electronic products in different stages are analyzed and evaluated through simultaneous connection of the electronic products in different states, the electronic products with the best money and the worst money can be screened out, and replenishment and unloading are carried out in a targeted manner, so that the optimal money can be kept in high-efficiency and orderly, and the poor money and the unloading are carried out so as to introduce new money, and the wholesale supervision effect of the electronic products is effectively improved.
Drawings
Fig. 1 is a flow chart of the method for supervising wholesale of electronic products.
Fig. 2 is a schematic block diagram of a supervision system applied to wholesale of electronic products.
Fig. 3 is a schematic structural diagram of the supervision device applied to wholesale of electronic products.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terminology used herein is for the purpose of describing embodiments and is not intended to limit and/or restrict the disclosure; it should be noted that the singular forms "a", "an" and "the" include plural forms as well, unless the context clearly indicates otherwise; moreover, although the terms "first," "second," etc. may be used herein to describe various elements, the elements are not limited by these terms, and these terms are merely used to distinguish one element from another element.
Referring to fig. 1, a flow chart of a supervision method applied to wholesale of electronic products according to an embodiment of the invention is shown. In the embodiment of the invention, the applied scene can be online electronic product wholesale, which is different from the existing scheme that only the electronic products are put on shelf and restocked based on the stock and trade conditions of the electronic products, and the whole flow of warehousing, putting on shelf and trade wholesale of the electronic products of different types cannot be dynamically monitored and early-warning prompt in a self-adaptive manner, so that the wholesale monitoring effect of the electronic products of different types is poor; the embodiment of the invention can realize the comprehensiveness and diversity of wholesale supervision of the electronic products, and further can effectively improve the overall effect of wholesale supervision of the electronic products;
The method for supervising the wholesale of the electronic products comprises the following specific steps:
monitoring and counting the warehousing conditions of the electronic products every day to obtain a warehousing set of the electronic products; performing numerical processing on each item of data in the warehouse-in set to obtain a first extraction set; the warehousing set comprises the product types, the warehousing quantity and the warehousing time of the electronic products; the method comprises the following specific steps of:
obtaining the product types, the warehousing quantity and the warehousing time of the centralized electronic products; product types of electronic products include, but are not limited to, electronic watches, smart phones, computers, and gaming machines;
matching the product type with a pre-constructed product association table to obtain a corresponding product association value and marking the product association value as CG; the product association table consists of different types of electronic products and corresponding product association values thereof, wherein the different types of electronic products are preset with a corresponding product association value; the product association value can be set according to the wholesale price of the electronic product;
it should be noted that the purpose of building the product association table is to implement the numeralization of different types of electronic products, so as to dynamically monitor and count the different types of electronic products;
Extracting numerical values in the warehouse-in quantity and marking the numerical values as RS; setting the warehousing time of the electronic product as a first timestamp;
the marked product association value, the warehouse-in quantity and the first timestamp form a first extraction set;
calculating and analyzing the first extraction set to obtain a first calculation set containing warehouse-in coefficients; comprising the following steps:
calculating each item of data marked in the first extraction set through a formula to obtain a warehousing coefficient RKX of the electronic product; the formula is rkx=cg RS;
in the embodiment of the invention, the warehousing coefficient is a numerical value which is used for analyzing the state of the electronic product when the electronic product is in stock by combining the product association value with the warehousing quantity;
and analyzing the warehouse-in coefficient:
obtaining a corresponding product judgment threshold according to the product type, and matching the warehouse-in coefficient with the product judgment threshold;
if the warehousing coefficient is not greater than m% of the product judgment threshold value, judging that the electronic product inventory of the type is insufficient and generating a first warehousing signal; m is a real number greater than zero, and m in the embodiment of the invention can take the value of 30; setting the electronic products of the type as first warehouse-in products according to the first warehouse-in signals;
if the warehousing coefficient is greater than m% of the product judgment threshold value and is not greater than (200-m)% of the product judgment threshold value, judging that the electronic product inventory of the type is normal and generating a second warehousing signal;
If the warehousing coefficient is greater than (200-m)% of the product judgment threshold value, judging that the type of electronic product is excessive in inventory and generating a third warehousing signal; setting the electronic product of the type as a second warehouse-in product according to the third warehouse-in signal;
the first warehousing product, the second warehousing product, the first warehousing signal, the second warehousing signal and the third warehousing signal form a warehousing analysis set;
it should be noted that, the electronic products of different product types correspond to a normal stock range, in order to avoid too little or too much stock quantity during wholesale of the electronic products, analysis and judgment need to be performed according to product judgment thresholds corresponding to different product types, and the values of the product judgment thresholds corresponding to different electronic products are set based on wholesale big data of several months or one year in the past;
the warehousing coefficients and the warehousing analysis set form a first calculation set;
according to the embodiment of the invention, the warehouse-in condition of the electronic products before wholesale is monitored and analyzed, the electronic products with insufficient stock and excessive stock are screened out, and the electronic products can be self-adaptively and reasonably restocked based on the follow-up on-shelf condition and transaction condition of the electronic products, so that the effect of restocking the electronic products is effectively improved, and the defect that the prior scheme can only be restocked based on the blind purpose of sales condition is overcome.
Monitoring and counting the on-shelf conditions of the electronic products every day to obtain an on-shelf set of the electronic products; performing numerical processing on each item of data in the upper rack set to obtain a second extraction set; the shelf set comprises a shelf region, shelf time and browsing amount of the electronic product; the specific steps of obtaining the second extraction set include:
acquiring a racking area, racking time and browsing amount of electronic products in a racking set;
setting different upper frame areas to correspond to different area weights, matching the upper frame areas in the upper frame set with all the upper frame areas to obtain corresponding area weights, and marking the corresponding area weights as QQ;
wherein the racking area includes, but is not limited to, a home page, a middle upper page, a middle lower page, and a lower page; the purpose of setting weights of different regions corresponding to different regions of different shelves is to modularly process and assign values to the regions of electronic display so as to monitor and analyze the regions with different exhibition effects;
it should be noted that, in the wholesale display page of the electronic product on the line, the exposure rate displayed on the first page is the largest, the browsing opportunity is the largest, and similarly, the exposure rate displayed on the lower page is the smallest, and the browsing opportunity is the smallest;
In the embodiment of the invention, the area where the electronic product is displayed is subjected to modularized treatment to independently monitor and analyze, so that the accuracy and the comprehensiveness of the analysis of the display state of the electronic product on the shelf can be effectively improved, and effective data support is provided for subsequent transaction adjustment and replenishment adjustment.
Extracting the numerical value of the browsing amount and marking the numerical value as LL; setting the time to be on shelf as a second timestamp;
acquiring the time difference between the second time stamp and the first time stamp and setting the time difference as a first time difference YS; the time difference is in hours;
the marked area weight, browsing amount, second time stamp and first time difference form a second extraction set;
calculating and analyzing the second extraction set to obtain a second calculation set containing the warehouse-in coefficients; comprising the following steps:
calculating each item of data marked in the second extraction set through a formula to obtain a shelf-up coefficient SJX of the electronic product; the formula is sjx=qq (a 1 LL-a2 ys+ 0.2537); a1 and a2 are different proportional coefficients and are both larger than zero, a1 can take a value of 0.648, and a2 can take a value of 0.324;
in the embodiment of the invention, the shelving coefficient is a numerical value for analyzing the shelving state of the electronic product by combining the area weights corresponding to different areas after the electronic product is put on shelf with the browsing amount and the shelving duration; the racking coefficient can be a negative number, and the smaller the racking coefficient is, the worse the racking state of the corresponding electronic product is; the corresponding putting-on judging ranges of the different types of electronic products are different, so that the different types of electronic products can be processed in a targeted manner; when the on-shelf coefficients are analyzed and judged, the value of the on-shelf judging range is still set according to the type of the corresponding electronic product and historical on-shelf big data;
Analyzing the racking coefficient, acquiring a corresponding racking judgment range according to the type of the product, and matching the racking coefficient with the racking judgment range;
if the shelving coefficient is smaller than the minimum value of the shelving judging range, judging that the display effect of the shelving electronic product is poor and generating a first shelving signal; setting the corresponding electronic product as a first shelf product according to the first shelf signal;
if the shelving coefficient is not smaller than the minimum value of the shelving determination range and not larger than the maximum value of the shelving determination range, judging that the display effect of the shelving electronic product is normal and generating a second shelving signal;
if the shelving coefficient is larger than the maximum value of the shelving judging range, judging that the display effect of the shelving electronic product is good and generating a third shelving signal; setting the corresponding electronic product as a second shelf product according to the third shelf signal;
the first shelf product, the second shelf product, the first shelf signal, the second shelf signal and the third shelf signal form a shelf analysis set;
the racking coefficient and the racking analysis set form a second calculation set;
according to the embodiment of the invention, the electronic products with poor display effect and good display effect are screened out by monitoring and analyzing the loading conditions of different electronic products in different loading display areas, so that data support can be provided for the analysis of the subsequent electronic product transaction conditions, and the diversity and the comprehensiveness of the wholesale transaction analysis of the electronic products are improved.
Monitoring and counting the trade conditions of the electronic products every day to obtain a trade set of the electronic products; performing numerical processing on each item of data in the transaction set to obtain a third extraction set; the transaction set comprises the number of orders in the electronic product, the number of products in the transaction, the number of non-orders in the transaction and the number of non-products in the transaction; the specific steps of obtaining the third extraction set include:
acquiring the number of orders, the number of products, the number of non-orders and the number of non-products of the electronic products in the transaction set;
respectively extracting the numerical values of the number of orders and the number of products to be delivered and marking the numerical values as CC and CS;
respectively extracting the numerical values of the number of the undeveloped orders and the number of the undeveloped products and marking the numerical values as DD and DC; the non-ordered quantity refers to an order which is ordered but not paid on the same day and an order which is added into a shopping cart but not paid on the same day;
the marked amount of orders, the number of products to be delivered, the number of non-orders to be delivered and the number of non-products to be delivered form a third extraction set;
calculating and analyzing the third extraction set to obtain a third calculation set containing the warehouse-in coefficients; comprising the following steps:
calculating each item of data marked in the third extraction set through a formula to obtain a transaction coefficient JYX of the electronic product; the formula is JYX=b1×CC×CS-b2×DD×DC; b1 and b2 are different proportionality coefficients and are both larger than zero, b1 can take the value of 5.634, and b2 can take the value of 1.525;
It should be noted that the transaction coefficient is a numerical value for analyzing the transaction condition of the transaction data of the electronic product by combining the transaction data and the data to be paid; the larger the transaction coefficient is, the better the transaction condition corresponding to wholesale of the electronic product is; when the transaction coefficient is analyzed and judged, the value of the transaction judging range is still set according to the type of the corresponding electronic product and historical transaction big data.
Analyzing the transaction coefficient, acquiring a corresponding transaction judgment range according to the product type, and matching the transaction coefficient with the transaction judgment range;
if the transaction coefficient is smaller than the minimum value of the transaction judging range, judging that the transaction result of the electronic product is poor and generating a first transaction signal; setting the electronic product corresponding to the product type as a first transaction product according to the first warehouse-in signal;
if the transaction coefficient is not smaller than the minimum value of the transaction judging range and not larger than the maximum value of the transaction judging range, judging that the transaction result of the electronic product is normal and generating a second transaction signal;
if the transaction coefficient is greater than the maximum value of the transaction judging range, judging that the transaction result of the electronic product is excellent and generating a third transaction signal; setting the electronic product corresponding to the product type as a second transaction product according to the third warehousing signal;
The first transaction product, the second transaction product, the first transaction signal, the second transaction signal and the third transaction signal form a transaction analysis set; the transaction coefficient and the transaction analysis set form a third calculation set;
the first computing set, the second computing set and the third computing set form a monitoring total set;
according to the embodiment of the invention, the electronic products with poor transaction effect and good transaction effect are screened out by monitoring and analyzing the transaction conditions of the electronic products of different types, so that data support can be provided for the subsequent replenishment warehouse entry of the electronic products of different types, and the rationality and the comprehensiveness of the replenishment warehouse entry in the wholesale process of the electronic products are improved.
Analyzing and prompting wholesale conditions of different types of electronic products according to a monitoring collection, and specifically, the method comprises the following steps:
acquiring a first calculation set, a second calculation set and a third calculation set in a monitoring total set;
matching the first warehouse-in product and the second warehouse-in product contained in the first calculation set, the first shelf-up product and the second shelf-up product contained in the second calculation set, and the first transaction product and the second transaction product contained in the third calculation set;
if the second warehouse-in product, the first shelf-up product and the first transaction product are the same electronic product, judging that the wholesale effect of the electronic product is poor and generating a shelf-down signal; adding one to the next number of the electronic product according to the next signal; counting the total number of the electronic products in the period of one week, arranging the electronic products in descending order, and setting the first electronic product as the lower frame product;
If the first warehouse-in product, the second shelf-up product and the second transaction product are the same electronic product, judging that the wholesale effect of the electronic product is good and generating a replenishment signal; adding one to the replenishment times of the electronic product according to the replenishment signal; counting the total number of replenishment of all electronic products in a week, arranging the electronic products in a descending order, and setting the first electronic product as a replenishment product;
the shelf-down signal and the replenishment signal as well as the shelf-down product and the replenishment product form an analysis set of electronic product wholesale, and corresponding early warning and prompt are sent to an administrator according to different signals in the analysis set, so that the administrator can timely carry out product shelf-down and product replenishment.
It should be noted that by monitoring and analyzing different processes of wholesale of different types of electronic products every day, screening out products with poor states and good states in different processes of the same day, and counting the monitoring conditions of different processes when wholesale of all types of electronic products in a week, the optimal and worst electronic products can be screened out, and replenishment and unloading can be performed in a targeted manner, so that the optimal money can be kept in high-efficient and orderly commodity feeding, and poor money and unloading can be performed so as to introduce new money;
According to the embodiment of the invention, through carrying out modularized treatment on the wholesale processes of different types of electronic products, firstly, the processes of different modules in the wholesale process are analyzed and monitored, and finally, the monitoring results of all the modules are combined and different early warning and prompting are implemented, so that the overall effect of wholesale supervision of the electronic products is effectively improved.
Referring to fig. 2, a schematic block diagram of a supervision system applied to wholesale of electronic products according to an embodiment of the present invention is shown. In this embodiment, the supervision system applied to wholesale of electronic products includes a warehouse-in module, an on-shelf module, a transaction module, a calculation module and a management module;
the warehousing module is used for monitoring and counting the warehousing conditions of the electronic products every day to obtain a warehousing set of the electronic products; performing numerical processing on each item of data in the warehouse-in set to obtain a first extraction set; the warehousing set comprises the product types, the warehousing quantity and the warehousing time of the electronic products;
the shelving module is used for monitoring and counting the shelving situation of the electronic products every day to obtain a shelving set of the electronic products; performing numerical processing on each item of data in the upper rack set to obtain a second extraction set; the shelf set comprises a shelf region, shelf time and browsing amount of the electronic product;
The transaction module is used for monitoring and counting the transaction condition of the electronic products every day to obtain a transaction set of the electronic products; performing numerical processing on each item of data in the transaction set to obtain a third extraction set; the transaction set comprises the number of orders in the electronic product, the number of products in the transaction, the number of non-orders in the transaction and the number of non-products in the transaction;
the calculation module is used for respectively calculating and analyzing the first extraction set, the second extraction set and the third extraction set to obtain a first calculation set containing the warehouse-in coefficients, a second calculation set containing the put-on coefficients and a third calculation set containing the warehouse-out coefficients; the first computing set, the second computing set and the third computing set form a monitoring total set;
and the management module is used for analyzing and prompting wholesale conditions of different types of electronic products according to the monitoring collection.
Referring to fig. 3, a schematic structural diagram of a supervision device applied to wholesale of electronic products according to an embodiment of the present invention is shown. In this embodiment, the supervision device applied to wholesale of electronic products may include a processor, a memory, a communication bus, and a communication interface, and may further include a computer program stored in the memory and executable on the processor.
The processor may be formed by an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be formed by a plurality of integrated circuits packaged with the same function or different functions, including one or more central processing units (Central Processing unit, CPU), a microprocessor, a digital processing chip, a combination of a graphics processor and various control chips, and the like. The processor is a control unit (control unit) of the electronic device, connects various components of the entire electronic device using various interfaces and lines, and executes various functions of the electronic device and processes data by running or executing programs or modules stored in a memory (e.g., a supervisory program applied to wholesale electronic products, etc.), and calling data stored in the memory.
The memory includes at least one type of readable storage medium including flash memory, a removable hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, etc. The memory may in some embodiments be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device. The memory may also be an external storage device of the electronic device in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the electronic device. The memory may also include both internal storage units and external storage devices of the electronic device. The memory may be used not only for storing application software installed in the electronic device and various types of data, such as codes applied to a supervisory program of wholesale of an electronic product, but also for temporarily storing data that has been output or is to be output.
The communication bus may be a peripheral component interconnect standard (peripheral componentinterconnect, PCI) bus or an extended industry standard architecture (extended industry standardarchitecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between said memory and at least one processor or the like.
The communication interface is used for communication between the electronic device and other devices, and comprises a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), or alternatively a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device and for displaying a visual user interface.
Fig. 3 shows only an electronic device with components, and it will be understood by those skilled in the art that the structure shown in fig. 3 is not limiting of the electronic device and may include fewer or more components than shown, or may combine certain components, or a different arrangement of components.
For example, although not shown, the electronic device may further include a power source (such as a battery) for powering the respective components, and the power source may be logically connected to the at least one processor through a power management device, so as to perform functions of charge management, discharge management, and power consumption management through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device may also include various sensors, bluetooth modules, wi-Fi modules, etc., which are not described in detail herein.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application. The supervisory program applied to electronic product wholesale stored in the memory in the electronic device is a combination of a plurality of signals, and when running in the processor, implementation and running of each step of the supervisory method applied to electronic product wholesale can be realized.
Specifically, the specific implementation method of the above signals by the processor may refer to descriptions of related steps in the corresponding embodiments of the drawings, which are not repeated herein.
The modules/units integrated in the electronic device may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the modules is merely a logical function division, and other division manners are possible when actually implemented.
The modules illustrated as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
Claims (10)
1. The supervision method applied to electronic product wholesale is characterized by comprising the following steps:
respectively monitoring and counting the warehousing condition, the shelving condition and the transaction condition of the electronic products every day to obtain a warehousing set, a shelving set and a transaction set of the electronic products;
Respectively carrying out numerical processing on each item of data in the warehouse-in set, the shelf set and the transaction set to obtain a first extraction set, a second extraction set and a third extraction set;
respectively calculating and analyzing the first extraction set, the second extraction set and the third extraction set to obtain a first calculation set, a second calculation set and a third calculation set;
the first calculation set comprises a warehouse-in coefficient and a warehouse-in analysis set; the step of obtaining the warehouse entry analysis set comprises the following steps: (1) Obtaining a corresponding product judgment threshold according to the product type, and matching the warehouse-in coefficient with the product judgment threshold; (2) If the warehousing coefficient is not greater than m% of the product judgment threshold value, judging that the electronic product inventory of the type is insufficient and generating a first warehousing signal; m is a real number greater than zero; setting the electronic products of the type as first warehouse-in products according to the first warehouse-in signals; (3) If the warehousing coefficient is greater than m% of the product judgment threshold value and is not greater than (200-m)% of the product judgment threshold value, judging that the electronic product inventory of the type is normal and generating a second warehousing signal; (4) If the warehousing coefficient is greater than (200-m)% of the product judgment threshold value, judging that the type of electronic product is excessive in inventory and generating a third warehousing signal; setting the electronic product of the type as a second warehouse-in product according to the third warehouse-in signal; (5) The first warehousing product, the second warehousing product, the first warehousing signal, the second warehousing signal and the third warehousing signal form a warehousing analysis set;
The second calculation set comprises a racking coefficient and a racking analysis set; the step of obtaining the set of overhead analysis includes: (1) Obtaining a corresponding shelving judging range according to the product type, and matching the shelving coefficient with the shelving judging range; (2) If the shelving coefficient is smaller than the minimum value of the shelving judging range, judging that the display effect of the shelving electronic product is poor and generating a first shelving signal; setting the corresponding electronic product as a first shelf product according to the first shelf signal; (3) If the shelving coefficient is not smaller than the minimum value of the shelving determination range and not larger than the maximum value of the shelving determination range, judging that the display effect of the shelving electronic product is normal and generating a second shelving signal; (4) If the shelving coefficient is larger than the maximum value of the shelving judging range, judging that the display effect of the shelving electronic product is good and generating a third shelving signal; setting the corresponding electronic product as a second shelf product according to the third shelf signal; (5) The first shelf product, the second shelf product, the first shelf signal, the second shelf signal and the third shelf signal form a shelf analysis set;
the third calculation set comprises a transaction coefficient and a transaction analysis set; the step of obtaining the transaction analysis set comprises: (1) Obtaining a corresponding transaction judging range according to the product type, and matching the transaction coefficient with the transaction judging range; (2) If the transaction coefficient is smaller than the minimum value of the transaction judging range, judging that the transaction result of the electronic product is poor and generating a first transaction signal; setting the electronic product corresponding to the product type as a first transaction product according to the first warehouse-in signal; (3) If the transaction coefficient is not smaller than the minimum value of the transaction judging range and not larger than the maximum value of the transaction judging range, judging that the transaction result of the electronic product is normal and generating a second transaction signal; (4) If the transaction coefficient is greater than the maximum value of the transaction judging range, judging that the transaction result of the electronic product is excellent and generating a third transaction signal; setting the electronic product corresponding to the product type as a second transaction product according to the third warehousing signal; (5) The first transaction product, the second transaction product, the first transaction signal, the second transaction signal and the third transaction signal form a transaction analysis set;
The supervision method applied to wholesale of the electronic products further comprises the steps of analyzing and prompting wholesale conditions of different types of electronic products according to the first calculation set, the second calculation set and the third calculation set in the monitoring total set; the steps of analyzing and prompting wholesale conditions of different types of electronic products comprise: (1) Matching the first warehouse-in product and the second warehouse-in product contained in the first calculation set, the first shelf-up product and the second shelf-up product contained in the second calculation set, and the first transaction product and the second transaction product contained in the third calculation set; (2) If the second warehouse-in product, the first shelf-up product and the first transaction product are the same electronic product, judging that the wholesale effect of the electronic product is poor and generating a shelf-down signal; adding one to the next number of the electronic product according to the next signal; counting the total number of the electronic products in the period of one week, arranging the electronic products in descending order, and setting the first electronic product as the lower frame product; (3) If the first warehouse-in product, the second shelf-up product and the second transaction product are the same electronic product, judging that the wholesale effect of the electronic product is good and generating a replenishment signal; adding one to the replenishment times of the electronic product according to the replenishment signal; counting the total number of replenishment of all electronic products in a week, arranging the electronic products in a descending order, and setting the first electronic product as a replenishment product; (4) The lower frame signal and the replenishment signal form an analysis set of electronic product wholesale, and corresponding early warning and prompt are sent to an administrator according to different signals in the analysis set.
2. The method for supervising wholesale application to electronic products according to claim 1, wherein the specific step of obtaining the first extraction set comprises:
obtaining corresponding product association values according to the product types of the electronic products in the warehouse-in set and marking; extracting a numerical value in the marked warehouse-in quantity; setting the warehousing time of the electronic product as a first timestamp;
the marked product association value, the number of warehouses, and the first timestamp constitute a first extraction set.
3. The supervision method applied to wholesale of electronic products according to claim 2, wherein each item of data in the first extraction set is subjected to simultaneous calculation to obtain a warehouse-in coefficient of the electronic products; the warehousing coefficient is a numerical value for analyzing the state of the electronic product when the electronic product is in stock by combining the product association value with the warehousing quantity;
and analyzing the warehouse-in coefficient to obtain a warehouse-in analysis set.
4. The method for monitoring wholesale of electronic products according to claim 3, wherein the specific step of obtaining the second extraction set comprises:
acquiring corresponding region weights according to the shelving regions of the electronic products in the shelving set and marking; extracting a numerical value of the marked browsing quantity; setting the time to be on shelf as a second timestamp; acquiring the time difference between the second time stamp and the first time stamp and setting the time difference as the first time difference; the labeled region weight, the browsing volume, the second timestamp, and the first time difference constitute a second extraction set.
5. The method for supervising wholesale application to an electronic product according to claim 4, wherein the on-shelf coefficients of the electronic product are obtained by performing simultaneous computation on each item of data in the second extraction set; the shelving coefficient is a numerical value for analyzing the shelving state of the electronic product by combining the area weights corresponding to different areas after the electronic product is put on shelf with the browsing amount and the shelving duration;
and analyzing the racking coefficient to obtain a racking analysis set.
6. The method for supervising wholesale application to an electronic product according to claim 5, wherein the specific step of obtaining the third extraction set comprises:
and respectively extracting the number of the orders, the number of the products to be processed, and the number of the products to be processed, wherein the number of the orders, the number of the products to be processed, and the number of the products to be processed are marked to form a third extraction set.
7. The method for supervising wholesale application of electronic products according to claim 6, wherein the transaction coefficients of the electronic products are obtained by performing simultaneous computation on each item of data in the third extraction set; the transaction coefficient is a numerical value for analyzing the transaction condition of the transaction data of the electronic product by combining the transaction data and the data to be paid;
And analyzing the transaction coefficients to obtain a transaction analysis set.
8. The method of claim 7, wherein the pre-warning and prompting of replenishment and removal of different types of electronic products is performed based on the first and second warehouse-in products in the first computing set, the first and second upper rack products in the second computing set, and the first and second transaction products in the third computing set.
9. A supervision system applied to electronic product wholesale, a supervision method applied to electronic product wholesale according to any one of claims 1 to 8, comprising:
the warehousing module is used for monitoring and counting the warehousing conditions of the electronic products every day to obtain a warehousing set of the electronic products; performing numerical processing on each item of data in the warehouse-in set to obtain a first extraction set; the warehousing set comprises the product types, the warehousing quantity and the warehousing time of the electronic products;
the shelving module is used for monitoring and counting the shelving situation of the electronic products every day to obtain a shelving set of the electronic products; performing numerical processing on each item of data in the upper rack set to obtain a second extraction set; the shelf set comprises a shelf region, shelf time and browsing amount of the electronic product;
The transaction module is used for monitoring and counting the transaction condition of the electronic products every day to obtain a transaction set of the electronic products; performing numerical processing on each item of data in the transaction set to obtain a third extraction set; the transaction set comprises the number of orders in the electronic product, the number of products in the transaction, the number of non-orders in the transaction and the number of non-products in the transaction;
the calculation module is used for respectively calculating and analyzing the first extraction set, the second extraction set and the third extraction set to obtain a first calculation set containing the warehouse-in coefficients, a second calculation set containing the put-on coefficients and a third calculation set containing the warehouse-out coefficients; the first computing set, the second computing set and the third computing set form a monitoring total set;
and the management module is used for analyzing and prompting wholesale conditions of different types of electronic products according to the monitoring collection.
10. The supervision device applied to electronic product wholesale is characterized by comprising at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of supervision of electronic product wholesale as claimed in any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210714390.3A CN114792222B (en) | 2022-06-23 | 2022-06-23 | Supervision method, system and device applied to wholesale of electronic products |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210714390.3A CN114792222B (en) | 2022-06-23 | 2022-06-23 | Supervision method, system and device applied to wholesale of electronic products |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114792222A CN114792222A (en) | 2022-07-26 |
| CN114792222B true CN114792222B (en) | 2023-05-30 |
Family
ID=82463715
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210714390.3A Active CN114792222B (en) | 2022-06-23 | 2022-06-23 | Supervision method, system and device applied to wholesale of electronic products |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114792222B (en) |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2008049033A1 (en) * | 2006-10-18 | 2008-04-24 | Kjell Roland Adstedt | System and method for demand driven collaborative procurement, logistics, and authenticity establishment of luxury commodities using virtual inventories |
| CN109544289B (en) * | 2018-11-15 | 2020-12-18 | 深圳市福尔科技有限公司 | Method and system for realizing online wholesale |
| CN112446658B (en) * | 2019-09-04 | 2024-07-19 | 北京京东乾石科技有限公司 | Method and device for shunting and loading storage articles |
| CN112330237A (en) * | 2020-05-20 | 2021-02-05 | 北京京东振世信息技术有限公司 | Warehousing method and device for articles and nonvolatile computer readable storage medium |
| CN113222704A (en) * | 2021-05-21 | 2021-08-06 | 刘天琼 | Wisdom supply chain digit DaaS trans-border electricity business service platform |
-
2022
- 2022-06-23 CN CN202210714390.3A patent/CN114792222B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN114792222A (en) | 2022-07-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20210174300A1 (en) | Commodity replenishment method and device | |
| Parthanadee et al. | Production efficiency improvement in batch production system using value stream mapping and simulation: a case study of the roasted and ground coffee industry | |
| CN110310057B (en) | Goods sorting and goods location processing method, device, equipment and storage medium thereof | |
| CN110097203A (en) | Inventory's dispatching method, inventory's dispatching device and computer readable storage medium | |
| CN107103446A (en) | Stock's dispatching method and device | |
| CN109886169B (en) | Article identification method, device, equipment and storage medium applied to unmanned container | |
| CN111242524A (en) | Method, system, equipment and storage medium for determining replenishment quantity of single article | |
| CN113592207A (en) | Robot-based mesh supply chain decision method, equipment and storage medium | |
| CN112381482A (en) | Material management method and device, electronic equipment and storage medium | |
| CN108255607A (en) | Task processing method, device, electric terminal and readable storage medium storing program for executing | |
| CN112184390A (en) | Electronic commerce commodity information management method and system based on cloud platform | |
| CN108922084A (en) | A kind of commodity recognition method and device | |
| CN104123303B (en) | A kind of method and device that data are provided | |
| CN114792222B (en) | Supervision method, system and device applied to wholesale of electronic products | |
| CN117235760A (en) | Encryption storage method and device for enterprise data, computer equipment and storage medium | |
| CN115311005B (en) | Fresh food supply and demand management method and device, electronic equipment and storage medium | |
| CN115330468B (en) | Data processing method and related device | |
| CN106779560A (en) | Method, system and electronic equipment for managing commodity | |
| CN115482051A (en) | Commodity management method, device and equipment based on ERP system and readable storage medium | |
| JP4867351B2 (en) | Product sorting system and product sorting method | |
| CN108027943B (en) | Method and system for generating scheduling data structure for promotion display space | |
| CN114358625A (en) | Method and device for distributing object streams, storage medium and electronic equipment | |
| CN108428174A (en) | Transaction funds method for early warning, server and storage medium | |
| CN111260444B (en) | Order issuing method, device and computer system for goods-free commodities | |
| CN116862574A (en) | Product demand prediction method, device, electronic equipment and readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| EE01 | Entry into force of recordation of patent licensing contract | ||
| EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20220726 Assignee: Shandong Academy of Sciences Yida Technology Consulting Co.,Ltd. Assignor: Shandong Shuyuan Information Technology Co.,Ltd. Contract record no.: X2024980010572 Denomination of invention: Regulatory methods, systems, and devices applied to wholesale of electronic products Granted publication date: 20230530 License type: Exclusive License Record date: 20240726 |