CN113159708A

CN113159708A - Early warning information generation method and device, readable storage medium and electronic equipment

Info

Publication number: CN113159708A
Application number: CN202110298128.0A
Authority: CN
Inventors: 曲悦
Original assignee: Beijing Jingdong Tuoxian Technology Co Ltd
Current assignee: Beijing Jingdong Tuoxian Technology Co Ltd
Priority date: 2021-03-19
Filing date: 2021-03-19
Publication date: 2021-07-23

Abstract

The disclosure relates to the technical field of computers, and provides an early warning information generation method and device, a computer storage medium and an electronic device. Wherein, the method comprises the following steps: acquiring current inventory data of the articles with the remaining shelf life longer than a first preset threshold; acquiring historical sales data of the articles, and predicting the daily average sales of the articles according to the historical sales data; determining a target sale period of the goods according to the current inventory data and the daily average sales volume; determining the temporary storage date of the article according to the expiration date of the article and the first preset threshold value; and determining the time difference between the temporary date and the current date, and generating the early warning information of the articles with the target sale period larger than the time difference. According to the method and the device, early warning of the article approaching the quality guarantee period can be realized based on the first preset threshold and the sales prediction of the article, and the timeliness and the accuracy of generation of early warning information are improved.

Description

Early warning information generation method and device, readable storage medium and electronic equipment

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to an early warning information generation method, an early warning information generation apparatus, a computer-readable storage medium, and an electronic device.

Background

In order to ensure the use safety of consumers, the commodities sold on the market cannot be overdue. Therefore, the commodity shelf life early warning reminding method can carry out shelf life early warning reminding on the commodity so as to guarantee the use safety of consumers and reduce the loss caused by the fact that the commodity cannot be sold by merchants due to expiration.

Taking the shelf life approaching early warning reminding as an example, in the related technology, according to the preset reminding time, when the remaining shelf life time falls within the reminding time, the shelf life approaching early warning is carried out on the medicine.

However, the accuracy and timeliness of the early warning method depend on the preset reminding time to a great extent, if the set reminding time is too short, the timeliness of the early warning is reduced, and the problem of unsafe is still likely to exist, and if the set reminding time is too long, the significance and value of the early warning reminding are not achieved.

It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.

Disclosure of Invention

The invention aims to provide a method and a device for generating early warning information, a computer readable storage medium and electronic equipment, so that timeliness and accuracy of early warning of the shelf life of an article are improved at least to a certain extent.

Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.

According to a first aspect of the present disclosure, a method for generating early warning information is provided, including:

acquiring current inventory data of the articles with the remaining shelf life longer than a first preset threshold;

obtaining historical sales data of the articles, and predicting the daily average sales of the articles according to the historical sales data;

determining a target sale period of the goods according to the current inventory data and the daily average sales volume;

determining the temporary storage date of the article according to the expiration date of the article and the first preset threshold;

and determining the time difference between the critical date and the current date, and generating the early warning information of the articles with the target sale period larger than the time difference.

In an exemplary embodiment of the disclosure, based on the foregoing scheme, the obtaining of the current inventory data of the items with the remaining shelf life greater than the first preset threshold includes:

acquiring the expiration date of each production batch corresponding to the stock unit of the article from the stock database on the basis of the stock unit;

determining the remaining shelf life duration corresponding to each production batch according to the time difference between the expiration date and the current date;

and acquiring current inventory data of a target production batch corresponding to the inventory unit of the article, wherein the target production batch comprises a production batch of which the remaining shelf life is longer than a first preset threshold.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the obtaining historical sales data of the item, and predicting a daily average sales of the item according to the historical sales data includes:

and acquiring historical sales data of each target production batch, and predicting the daily average sales of each target production batch corresponding to the article according to the historical sales data of each target production batch.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, obtaining historical sales data of each target production lot, and predicting a daily average sales of each target production lot corresponding to the article according to the historical sales data of each target production lot, includes:

for each of the target production lots, performing the following process:

acquiring first historical sales data of the articles in the latest first preset time, and predicting first daily average sales data of the target production batch according to the first historical sales data;

determining a temporary date corresponding to the target production batch according to the expiration date corresponding to the target production batch and the first preset threshold;

determining a temporary date corresponding to the target production batch and a time interval corresponding to the current date, and determining a historical synchronization time interval corresponding to the time interval as a target historical time interval corresponding to the target production batch;

acquiring second historical sales data in the target historical time interval, and predicting second daily average sales data of the target production batch according to the second historical sales data;

acquiring a first product corresponding to the first daily average sales data and a first weight, and a second product corresponding to the second daily average sales data and a second weight, and determining the daily average sales of the target production batch according to the sum of the first product and the second product;

wherein the first weight and the second weight are non-negative numbers and a sum of the first weight and the second weight is 1.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the determining a target sale period of the item according to the current inventory data and the average daily sales amount includes:

determining a period to be sold of each target production batch according to the current inventory data of each target production batch and the daily average sales volume of each target production batch;

sequencing the target production batches in an ascending order according to the due date corresponding to each target production batch;

and determining the sum of the period to be sold of the target production batch before the current target production batch in the due date sequence and the period to be sold of the current target production batch to obtain the target sales period of the current target production batch.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the determining the temporary storage date of the item according to the expiration date of the item and the first preset threshold includes:

determining the temporary date of each target production batch according to the expiration date of each target production batch corresponding to the stock quantity unit of the article and the first preset threshold;

the determining the time difference between the critical date and the current date and generating the early warning information of the article with the target sale period larger than the time difference comprises the following steps:

and determining the time difference between the temporary date and the current date of each target production batch, and generating the early warning information of the target production batch with the target sale period being greater than the time difference.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, after generating the warning information of the article with the target sale period being greater than the time difference, the method further includes:

storing the early warning information of the current date so as to send the early warning information of the current date to a client;

wherein the early warning information comprises: one or more of the inventory unit identifier of the article, the target production batch identifier, the target sales cycle corresponding to the target production batch, the current inventory data corresponding to the target production batch, the remaining shelf life duration corresponding to the target production batch, and the time difference corresponding to the target production batch.

According to a second aspect of the present disclosure, there is provided an early warning information generating apparatus, including:

the inventory data acquisition module is configured to acquire current inventory data of the articles with the remaining shelf life longer than a first preset threshold;

the daily average sales amount prediction module is configured to acquire historical sales amount data of the articles and predict the daily average sales amount of the articles according to the historical sales amount data;

a target sale period determination module configured to determine a target sale period of the item according to the current inventory data and the daily average sales volume;

a warranty date determination module configured to determine a warranty date of the item according to the expiration date of the item and the first preset threshold;

and the early warning information generation module is configured to determine a time difference value between the temporary date and the current date and generate early warning information of the articles with the target sale period larger than the time difference value.

According to a third aspect of the present disclosure, there is provided a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements the warning information generating method according to the first aspect of the above embodiments.

According to a fourth aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including: a processor; and a storage device configured to store one or more programs, which when executed by the one or more processors, cause the one or more processors to implement the warning information generating method according to the first aspect of the embodiments.

As can be seen from the foregoing technical solutions, the warning information generating method, the warning information generating apparatus, and the computer-readable storage medium and the electronic device for implementing the warning information generating method in the exemplary embodiment of the present disclosure have at least the following advantages and positive effects:

in the technical scheme provided by some embodiments of the present disclosure, first, current inventory data of an article whose remaining shelf life duration is greater than a first preset threshold is obtained; secondly, predicting sales data of the articles, so as to determine the sales period of the articles according to the current stock data and the sales data of the articles; and then, according to the expiration date of the article and a first preset threshold value, determining the temporary date of the article, further determining the time difference between the temporary date and the current date, and finally generating the early warning information of the article with the target sale period being larger than the time difference. Compared with the related art, on one hand, the method and the system can realize early warning reminding before the shelf life of the article based on the determined temporary guarantee date, so that the timeliness of early warning when the shelf life of the article is close to is improved; on the other hand, the method combines the temporary guarantee date with the commodity sales prediction, and can improve the accuracy and effectiveness of commodity early warning; in another aspect, the article sales service system can remind a merchant of reasonably selling the article before the pre-guaranteed date based on early warning of the article with the target sales period being greater than the time difference between the pre-guaranteed date and the current date, and the pre-guaranteed date and the expiration date have the time difference of the first preset threshold value, so that the article usage safety of the consumer can be further ensured.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.

Fig. 1 shows a schematic flow chart of an early warning information generation method in an exemplary embodiment of the present disclosure;

FIG. 2 is a flow chart illustrating a method for obtaining current inventory data for items having a remaining shelf life greater than a first predetermined threshold in an exemplary embodiment of the present disclosure;

FIG. 3 is a diagram illustrating a relationship between an early warning start date, a temporary storage date and an expiration date on a time axis according to an exemplary embodiment of the disclosure;

FIG. 4 illustrates a flow chart diagram of a method of predicting the average daily sales of an item in an exemplary embodiment of the present disclosure;

FIG. 5 illustrates a flow chart diagram of a method of determining a target sales cycle in an exemplary embodiment of the present disclosure;

fig. 6 is a schematic flow chart diagram illustrating a method for generating early warning information for a drug in an exemplary embodiment of the disclosure;

fig. 7 is a schematic structural diagram of an early warning information generation apparatus according to an exemplary embodiment of the present disclosure;

FIG. 8 shows a schematic diagram of a structure of a computer storage medium in an exemplary embodiment of the disclosure; and the number of the first and second groups,

fig. 9 shows a schematic structural diagram of an electronic device in an exemplary embodiment of the present disclosure.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.

The terms "a," "an," "the," and "said" are used in this specification to denote the presence of one or more elements/components/parts/etc.; the terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements/components/etc. other than the listed elements/components/etc.; the terms "first" and "second", etc. are used merely as labels, and are not limiting on the number of their objects.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities.

In the related technology, when the shelf life approaching early warning is carried out on an article, according to the preset reminding time length, when the current time is less than or equal to the preset reminding time length from the expiration time length of the article, the shelf life approaching early warning is carried out on the article.

However, the accuracy, timeliness and effectiveness of the method depend on the preset reminding time to a great extent, if the preset reminding time is too short, the timeliness of early warning is affected, a merchant cannot assist in reasonably promoting sales of articles close to the shelf life in time, the problem that the merchant is lost due to the fact that commodities cannot be processed in time still exists, if the set reminding time is too long, the merchant still cannot determine whether sales promotion and other processing are needed, the meaning and value of early warning reminding are lost, and the accuracy of early warning reminding is reduced.

In the embodiments of the present disclosure, a method for generating warning information is provided first, which overcomes the above-mentioned drawbacks in the related art at least to some extent.

Step S110, obtaining the current inventory data of the articles with the remaining shelf life longer than a first preset threshold;

step S120, obtaining historical sales data of the articles, and predicting the daily average sales of the articles according to the historical sales data;

step S130, determining a target sale period of the goods according to the current inventory data and the daily average sales volume;

step S140, determining the temporary storage date of the article according to the expiration date of the article and the first preset threshold value;

and S150, determining the time difference between the temporary storage date and the current date, and generating the early warning information of the articles with the target sale period larger than the time difference.

In the technical solution provided in the embodiment shown in fig. 1, first, current inventory data of the articles whose remaining shelf life duration is greater than a first preset threshold is obtained; secondly, predicting sales data of the articles, so as to determine the sales period of the articles according to the current stock data and the sales data of the articles; and then, according to the expiration date of the article and a first preset threshold value, determining the temporary date of the article, further determining the time difference between the temporary date and the current date, and finally generating the early warning information of the article with the target sale period being larger than the time difference. Compared with the related art, on one hand, the method and the system can realize early warning reminding before the shelf life of the article based on the determined temporary guarantee date, so that the timeliness of early warning when the shelf life of the article is close to is improved; on the other hand, the method combines the temporary guarantee date with the commodity sales prediction, and can improve the accuracy and effectiveness of commodity early warning; in another aspect, the article sales service system can remind a merchant of reasonably selling the article before the pre-guaranteed date based on early warning of the article with the target sales period being greater than the time difference between the pre-guaranteed date and the current date, and the pre-guaranteed date and the expiration date have the time difference of the first preset threshold value, so that the article usage safety of the consumer can be further ensured.

The following detailed description of the various steps in the example shown in fig. 1:

in step S110, current inventory data of the items with the remaining shelf life longer than a first preset threshold is obtained.

Wherein the remaining shelf life duration may be determined by a time difference between the current date and the expiration date. For example, if the current date is 2021.3.1 and the expiration date of the item is 2021.3.31, the remaining duration of the shelf life is 30 days. The first preset threshold value can be self-defined according to requirements. For example, the first preset threshold may be configured to be 90 days.

In an exemplary embodiment, for each item in the inventory database, the current inventory data of the production lot with the remaining shelf life longer than the first preset threshold may be obtained based on the production lot corresponding to the inventory unit.

For example, fig. 2 is a flow chart illustrating a method for obtaining current inventory data of an item having a remaining shelf life greater than a first preset threshold according to an exemplary embodiment of the present disclosure. Referring to fig. 2, the method may include steps S210 to S230. Wherein:

in step S210, the expiration date of each production lot corresponding to the stock quantity unit of the item is acquired from the stock quantity database on the basis of the stock quantity unit.

In an exemplary embodiment, the inventory database stores inventory information for items based on units of inventory, production lots, production dates, expiration dates, current inventory levels.

The Stock Keeping Unit (SKU), that is, the Unit of Stock in/out measurement, may be a Unit of a member, a box, a tray, or the like, and the SKU is a physically inseparable Stock keeping Unit. For example, for a drug, different measurement units of a drug with the same name correspond to different SKUs, for example, boxed drug A and bagged drug A correspond to SKU1 and SKU2, respectively. Taking clothing as an example, different colors and different sizes of the same type of clothing correspond to different SKU codes.

At present, for articles, in order to ensure food safety and protect physical health of consumers, sales information and storage information of sold commodities need to be recorded in a database. For example, a pharmacy has strict management on medicines and must meet GSP (Good Supply Practice, pharmaceutical product quality management) regulations, so that the database clearly records the sales and storage information of the medicines.

For items, the same SKU will correspond to different expiration dates due to different production lots. For example, in step S210, the expiration date of each production lot corresponding to the stock quantity unit of the item may be obtained from the stock quantity database.

In step S220, for each production lot, the remaining shelf life duration corresponding to the production lot is determined according to the time difference between the expiration date and the current date.

In an exemplary embodiment, the production time and expiration time may be uniquely determined based on the unit of inventory and the production lot. The remaining shelf life may include the number of days the current date is from the expiration date.

Different production batches correspond to different expiration times, so that the remaining shelf life durations of different production batches are different. Therefore, for each production batch, the remaining shelf life duration corresponding to the production batch can be determined according to the time difference between the corresponding expiration date and the current date.

In step S230, the current inventory data of the target production lot corresponding to the inventory unit of the item is obtained.

The target production batches comprise production batches with the remaining shelf life longer than a first preset threshold value.

Through the steps S210 to S230, the remaining shelf-life durations of different production batches corresponding to the same stock unit can be determined based on the stock unit and the production batch, the current stock data of the production batch with the remaining shelf-life duration greater than the first preset threshold is obtained, and whether the early warning information of the production batch needs to be generated is determined according to the subsequent steps 110 to S140, so that the timeliness and the accuracy of the shelf-life early warning are improved.

In the present disclosure, the specific implementation of step S110 may also be: and acquiring the current inventory data of the articles with the shelf life remaining time longer than a first preset threshold and less than or equal to a second preset threshold. The first preset threshold may be used to determine the temporary date of the item, that is, the date before the expiration date is the first preset threshold may be determined as the temporary date of the item.

The second preset threshold may be used to determine a start date of the pre-warning treatment for the article, that is, when the shelf life pre-warning treatment for the article is required to be started may be determined according to the second preset threshold. Specifically, the date which is a second preset threshold from the expiration date and is before the expiration date may be a start date of the pre-warning process. That is to say, the start date of the article to be subjected to the early warning processing may be determined according to the expiration period of the article and the second preset threshold, and then, when the early warning processing operation is performed, if the current date is the same as or after the start date of the article to be subjected to the early warning processing, that is, when the early warning processing is performed, if the time difference between the current date corresponding to the early warning processing operation and the temporary date corresponding to the article is less than or equal to the second preset threshold, the subsequent processing of steps S120 to S140 may be performed on the article to determine whether the early warning information of the article is generated.

For example, the target production lot in step S230 may include a production lot with a remaining shelf life greater than a first preset threshold and less than or equal to a second preset threshold.

For example, if the current date is within the time interval corresponding to the start date and the temporary guarantee date of the article to be early-warned, the article can be subjected to subsequent early-warning processing to determine whether the early-warning information of the article needs to be generated, and according to the early-warning processing method and the early-warning device, the accuracy of early warning can be improved and the problem of early warning or too late early warning can be avoided by determining the date to be early-warned and the temporary guarantee date; the start date of the pre-warning process may also be not considered, and only the temporary date is considered, that is, if the current date is before the temporary date of a certain article, the subsequent pre-warning process is performed on the article to determine whether the pre-warning information of the article needs to be generated, which is not limited in this exemplary embodiment.

It should be noted that both the first preset threshold and the second preset threshold can be customized according to the requirement. The second preset threshold value can also be determined by the sum of the first preset threshold value and a third preset threshold value, and the third preset threshold value can be used for determining a time difference value between a starting date to be early-warned and an adjacent date. According to the method and the device, early warning treatment can be carried out before the guarantee date, so that timeliness and effectiveness of early warning of the shelf life of the article are improved. And for the articles with the remaining shelf life less than the first preset threshold, the corresponding early warning reminding information can be directly generated without performing the subsequent processing from step S220 to step S240.

For example, fig. 3 shows a schematic diagram of a start date, a temporary storage date and an expiration date of the pre-warning process in the time axis according to an exemplary embodiment of the disclosure. In fig. 3, for example, a drug a SKU1 includes a lot number 001 and a lot number 002, the first preset threshold is 90 days, and the second preset threshold is 180 days, wherein the expiration date of the lot number 001 is 2021, 6 and 30 days, and the expiration date of the lot number 002 is 2021, 4 and 30 months. For the 001 batch number, the initial date to be subjected to early warning processing is determined to be 2021 year 1 month 2 according to a second preset threshold, and the temporary storage date is determined to be 2021 year 4 month 2 according to a first preset threshold; for the 002 batch number, the starting date of the pre-warning treatment to be performed is determined to be 11/1/2020/s according to the second preset threshold, and the temporary storage date is determined to be 1/30/2021/s according to the first preset threshold.

For example, when the warning operation is performed on any date in the time interval corresponding to the date from 11/month 1/2020 to 1/month 30/2021, the current stock amount data of the 002 lot numbers can be acquired, and the warning process can be performed on the 002 lot numbers. At any date from 1/2/2021 to 4/2/2021, the current inventory data of 001 lot numbers can be acquired to be subjected to the subsequent warning processing. On the other hand, when the warning operation is performed on any date between 11/month 1/2020 and 2021/month 2, since the start date to be warned of 001 lot number has not been reached, only the current stock amount data of 002 lot number can be acquired. Of course, for the 002 lot numbers, if the warning operation is performed at any date before 1 month and 30 days 2021, the current stock amount data of the 002 lot numbers can be acquired. For the 001 lot number, if the warning operation is performed at any date before 4/12/2021, the current stock quantity data of the 001 lot number can be acquired.

With continued reference to fig. 1, in step S120, historical sales data of the item is obtained, and the average daily sales of the item is predicted according to the historical sales data.

For example, the specific implementation manner of step S120 may be to obtain historical sales data of each target production lot, and predict the average daily sales of each target production lot corresponding to the article according to the historical sales data of each target production lot. The target production batches can include production batches with the remaining shelf life length greater than a first preset threshold, and also include production batches with the remaining shelf life length greater than the first preset threshold and less than or equal to a second preset threshold.

For each target production lot, the average daily sales can be predicted with reference to the method of fig. 4. Specifically, steps S410 to S450 may be included.

In step S410, first historical sales data of the articles in the latest first preset time is obtained, and first daily average sales data of the target production lot is predicted according to the first historical sales data.

The first preset time can be customized according to requirements, for example, the first preset time can be within 30 days, that is, sales data of the article in the last 30 days is obtained and is used as first historical sales data. The database stores sales data for the items based on the date of sale, SKU number, quantity sold, etc. First historical sales data for the item over a recent first preset time may be obtained from the database.

Predicting the first daily average sales data for the target production lot from the first historical sales data may include: and determining historical daily average sales data according to the ratio of the first historical sales data to the first preset time, and determining the historical daily average sales data as the first daily average sales data of the target production batch. That is, the daily average sales data of the items in the first preset time may be determined as the first historical efficiency data of each target production lot, that is, the first daily average sales data of each target production lot may be the same for the same SKU, for example, when the sales in the last 30 days is 60000, the first daily average sales data of each target production lot may be 60000/30-2000.

Next, in step S420, a temporary storage date corresponding to the target production lot is determined according to the expiration date corresponding to the target production lot and a first preset threshold.

For example, the expiration date corresponding to the target production lot may be a first preset threshold and the date before the expiration date is determined as the temporary date corresponding to the target production lot.

In step S430, time intervals corresponding to the temporal coverage and the current date corresponding to the target production lot are determined, and the historical synchronization time interval corresponding to the time interval is determined as the target historical time interval corresponding to the target production lot.

In step S440, second historical sales data within the target historical time interval are obtained, and second daily average sales data of the target production lot are predicted according to the second historical sales data.

For example, after the guaranteed date corresponding to the target production lot is determined, the last-year same-period sales data of the time interval corresponding to the current date and the guaranteed date may be obtained, the last-year same-period average daily sales data is obtained according to the ratio of the last-year same-period sales data to the time length of the time interval, and the last-year same-period average daily sales data is determined as the second-day average sales data.

For example, if the provisional date is 28/2/2021 and the due date is 28/5/2021, sales data between 28/2/2020 and 28/5/2020 can be acquired, and the sales data is divided by 90 to obtain average sales data for the same date in the last year, which is used as the second average sales data for the target production lot.

In step S450, a first product corresponding to the first daily average sales data and the first weight and a second product corresponding to the second daily average sales data and the second weight are obtained, and the daily average sales of the target production lot is determined according to a sum of the first product and the second product. Wherein the first weight and the second weight are non-negative numbers and the sum of the first weight and the second weight is 1.

For example, the first daily average sales data may be a, the second daily average sales data may be b, and the daily average sales corresponding to the target production lot is P, where P is a × i + b × (1-i), where i is the first weight.

Through the above steps S410 to S450, the daily average sales amount of each target production lot corresponding to the stock quantity unit can be determined.

With continued reference to fig. 1, in step S130, a target sale period of the item is determined based on the current inventory data and the daily average sales volume.

For example, the specific implementation manner of step S130 may be that, for each target production lot corresponding to the stock unit of the item, the target sales cycle of each target production lot corresponding to the stock unit is determined according to the current stock data and the daily average sales volume of the target production lot.

Fig. 5 shows a flowchart of a method for determining a target sales cycle in an exemplary embodiment of the present disclosure. Referring to fig. 5, the method may include steps S510 to S530.

In step S510, a to-be-sold period of each target production lot is determined according to the current inventory data of each target production lot and the daily average sales volume of each target production lot.

For example, for each target production lot, the ratio of the current inventory data of the target production lot to the average daily sales volume of the target production lot may be determined as the to-be-sold period of the target production lot. That is, the period to be sold is the current stock quantity divided by the daily average sales volume.

In step S520, the target production lots are sorted in ascending order according to the expiration date corresponding to each target production lot.

For example, each target production lot may have a different expiration date, and the target production lots may be sorted in ascending order, i.e., with an earlier expiration date in front and a later expiration date in back, as the expiration dates for the target production lots.

In step S530, for the current target production batch, the sum of the to-be-sold period of the target production batch with the expiration date being sorted before the current target production batch and the to-be-sold period of the current target production batch is determined to obtain the target sale period of the current target production batch.

In an exemplary embodiment, the goal sale period may be understood as how long the goal production lot needs to be sold out, i.e. the time length of the goal production lot when it is sold out.

For example, the article may be sold according to the first-in-first-out principle, the production lot may be sold first, the production lot may be sold later, and the multiple target production lots for the same article SKU may have a time for selling the target production lot later than the time for selling the target production lot before the target production lot (i.e., the target sales cycle of each target production lot is equal to the waiting sales cycle of the target production lot with the expiration date earlier than the target production lot number and the waiting sales cycle of the target production lot), so as to determine the time for selling the target production lot.

It should be noted that, when the stock unit corresponds to one target production batch, the stock unit may directly determine the period to be sold of the target production batch as the corresponding target sales period without sorting. When the stock unit is corresponding to a plurality of target production batches, sorting can be performed, and the target sales cycle of the target production batch sorted at 1 st is the corresponding to-be-sold cycle.

In step S140, a temporary storage date of the item is determined according to the expiration date of the item and the first preset threshold.

The first preset threshold and the temporary storage date have been described previously, and are not described herein again.

For example, the specific implementation manner of step S140 may be to determine the temporary storage date of each target production lot according to the expiration date of each target production lot corresponding to the stock quantity unit of the item and the first preset threshold. As shown by the 001 lot number and the 002 lot number in FIG. 2, different lots of the same stock quantity unit of the same item have different due dates and therefore have different corresponding temporary dates.

Next, in step S150, a time difference between the provisional date and the current date is determined, and warning information of the item having the target sale period greater than the time difference is generated.

For example, the specific implementation manner of step S150 may be to determine a time difference between the temporary date and the current date of each target production lot, and generate the warning information of the target production lot with the target sales cycle greater than the time difference.

After the early warning information of the article with the target sale period being larger than the time difference value between the temporary date and the current date is generated, the early warning information of the current date can be stored so as to send the early warning information of the current date to the client.

Wherein, early warning information includes: the storage unit identification of the article, the target production batch identification, the target sale period corresponding to the target production batch, the current storage data corresponding to the target production batch, the remaining time of the quality guarantee period corresponding to the target production batch, and the time difference between the temporary guarantee date and the current date corresponding to the target production batch. The target production batches in the early warning information comprise target production batches with target sale periods larger than the time difference between the temporary date and the current date.

In an exemplary embodiment, the warning information may be automatically produced according to steps S110 to S150 at a preset time point. Here, the preset time point may be understood as the current date, for example, 5 am/day may be set to obtain the current inventory data from the inventory database, and then generate the warning information according to steps S110 to S150, and store the generated warning information in the data table, as shown in table 1 below. The early warning date in table 1 may be understood as the current date of the early warning operation. For example, the advance warning date 2021-01-01 may be understood as the advance warning operation performed on 1/2021, and when the advance warning operation is performed according to steps S110 to S150, the current date is 1/2021. The remaining temporary storage time is the time from the current date to the temporary storage date, and the selling-out period is the target selling period.

Table 1 early warning information storage data table

After the early warning information of each time is stored in the data table, as the historical early warning information can be recorded in the data table, the early warning information of which the early warning date is equal to the current date in the data table can be read, and the early warning information of the current date is sent to the client. For example, if the current date is 2021 year, 1 month and 1 day, the warning information of the warning date equal to 2021-01-01 can be read, and the following table 2 can be obtained.

TABLE 2 Pre-alarm information for the current date

SKU	Production batch number	Remaining duration of the temporary protection	Length of remaining shelf life	Current amount of stock	Sold out period
						10000	2020100701	70	160	87	90
10000	2020100702	70	160	98	97
						20000	2020100401	30	120	231	65

Illustratively, text warning information can also be sent to the client, such as: drug a, drug SKU: 10000, production lot number: 2020100701, the temporary storage is reached after 70 days, the expiration is out after 160 days, the current stock is 87, and the sale is expected to be finished after 90 days. For another example, in fig. 3, if the warning operation is performed on 1/2/2021, that is, the current date is 2021-01-02, and the stock of 001 production lot is 87, the expected number of sales is 60, the stock of 002 production lot is 223, and the expected number of sales is 120, the warning information may be:

medicine preparation: a, production batch number: 002, the stock reaches the temporary storage after 28 days, and is expired after 119 days, the current stock is 87, and the stock is expected to be sold out after 60 days.

Medicine preparation: a, production batch number: 001, arriving at the temporary storage after 90 days, expiring after 180 days, the current stock is 223, and the sale is expected to be finished in 120 days.

In the exemplary embodiment of the disclosure, based on the production batches, the current inventory data and sales forecast data of the production batches are combined, so that whether each production batch can be sold out before the shelf life is approached can be pre-warned in time, a customer is reminded whether to process the goods reasonably in time, and the timeliness and effectiveness of the shelf life pre-warning of the goods are improved. For example, the user is reminded to carry out sales promotion processing on products which cannot be sold out before the temporary guarantee date in time so as to avoid the condition that the articles are overdue, and meanwhile, because the temporary guarantee date has a period of time from the expiration date, if the user can sell out on the temporary guarantee date, the health and safety of the consumer can be guaranteed, and the consumer can use the articles before the expiration date. Meanwhile, when the sales volume is predicted, the accuracy of sales volume prediction can be improved by using the recent historical sales volume data and the historical sales volume data in the same period of the last year, and the accuracy of generated early warning information is further improved.

Further, fig. 6 shows a flowchart of a method for generating drug warning information in an exemplary embodiment of the present disclosure. Referring to fig. 6, the method may include steps S610 to S650.

In step S610, a production lot having a remaining shelf life of less than or equal to a second preset threshold is obtained for each pharmaceutical stock quantity unit and each production lot number corresponding thereto based on the inventory data table.

For example, the "remaining shelf life time" may be obtained by subtracting the "current date from the" expiration date "for each medicine SKU and production lot number based on the inventory data table, and if the remaining shelf life time is less than or equal to M + N, the production lot number is determined as the production lot number of the medicine to be warned, and the expiration date, the temporary storage date (expiration date-N), the remaining shelf life time (expiration date-current date), the remaining temporary storage time (temporary storage date-current date), and the current inventory of the production lot number are obtained. Where N is configured as a "drug expiration period" (l may be understood as a drug that has expired for N days, e.g., N90 days), M is configured as a "drug clinical period" (may be understood as a drug that will reach a clinical date after M days, e.g., M90 days), and M and N may be custom configured according to actual needs of the pharmacy.

It should be noted that N may be understood as the first preset threshold, and M + N may be understood as the second preset threshold.

In step S620, the average daily sales volume of the production lot with the remaining shelf life less than or equal to the second preset threshold is predicted.

For example, data of the last 30 days from the current date can be screened out based on the sales history data of the last 1 year, and the daily average sales volume of each medicine of the last 30 days can be calculated; acquiring the same date of the last year in the 'temporary storage date' interval corresponding to the 'current date' and the production batch number of the medicine, and calculating average daily sales data to obtain the same date of the last year in the temporary storage period (namely the time length from the current date to the temporary storage date) of the medicine; configuring a weighting coefficient i (for example, 0.5), and calculating a predicted sales amount by using the "average sales amount in the last 30 days" and the "average sales amount in the same period in the last year" of the temporary protection period, for example, if the predicted sales amount is P, then P is the average sales amount in the last 30 days i + the average sales amount in the same period in the last year of the temporary protection period (1-i);

in step S630, the sold-out period of the medicine and the corresponding production batch is determined according to the daily average sales volume of the production batch corresponding to each medicine, and the medicine and the corresponding production batch with the sold-out period greater than the medicine temporary guarantee period are determined.

For example, shelf life early warning can be performed on all drugs in a drug library, so that drug SKUs can be grouped, and each group is sorted in a positive order according to expiration time; calculating the period to be sold of each production batch number of each medicine, wherein the period to be sold is the current stock and the predicted sales P; and then calculating the selling-out period of each production batch number of each medicine, wherein a pharmacy can sell the medicines according to a first-in first-out principle, the production batch number can be sold out first when the production batch number is early, the production batch number can be sold out after the production batch number is finished, and for the condition that the remaining time of the quality guarantee period of a plurality of production batch numbers of the same medicine SKU is less than or equal to a second preset threshold, the selling-out time of the later production batch number is the time for selling out the production batch number after the selling-out time of the previous production batch number (namely, the selling-out period of each batch number is equal to the sum of the selling-out period of the production batch number with the expiration date being earlier than the sum of the selling-waiting period of the production batch number and the selling-waiting period of the production batch number), so that the selling-out period of each production batch number corresponding to each medicine can be calculated.

In step S640, for each medicine SKU, data corresponding to the production lot whose sold-out period is greater than the temporary guarantee period is obtained, and the warning information is generated.

The early warning information may include a medicine name, a medicine SKU, a production lot of which the sold-out period corresponding to the medicine SKU is greater than the temporary storage period, the temporary storage remaining time, the shelf life remaining time, the current stock, the sold-out period, and the like of the production lot.

In step S650, the warning information is stored according to the warning date, the warning information whose warning date is equal to the current date is read, and the warning information is sent to the client.

For example, the early warning information corresponding to each early warning date may be stored according to the early warning date, the stored format is as in table 1, and since the early warning information corresponding to each early warning date is stored, the database may store historical early warning information, and the early warning information whose early warning date is equal to the current date may be read to obtain the early warning information of the current date, as in table 2 above.

Those skilled in the art will appreciate that all or part of the steps implementing the above embodiments are implemented as computer programs executed by a CPU. The computer program, when executed by the CPU, performs the functions defined by the method provided by the present invention. The program may be stored in a computer readable storage medium, which may be a read-only memory, a magnetic or optical disk, or the like.

Furthermore, it should be noted that the above-mentioned figures are only schematic illustrations of the processes involved in the method according to exemplary embodiments of the invention, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.

Further, fig. 7 shows a schematic structural diagram of an early warning information generating apparatus in an exemplary embodiment of the present disclosure. Referring to fig. 7, the apparatus may include: the system comprises an inventory data acquisition module 710, a daily average sales volume prediction module 720, a target sales period determination module 730, an adjacent date determination module 740 and an early warning information generation module 750. Wherein:

an inventory data obtaining module 710 configured to obtain current inventory data of the articles with the remaining shelf life longer than a first preset threshold;

a daily average sales predicting module 720, configured to obtain historical sales data of the item, and predict daily average sales of the item according to the historical sales data;

a target sale period determination module 730 configured to determine a target sale period of the item according to the current inventory data and the daily average sales volume;

a warranty date determination module 740 configured to determine a warranty date of the item according to the expiration date of the item and the first preset threshold;

an early warning information generating module 750 configured to determine a time difference between the critical date and the current date, and generate early warning information for the item with the target sale period greater than the time difference.

In an exemplary embodiment of the disclosure, based on the foregoing solution, the stock quantity data obtaining module 710 obtains the current stock quantity data of the articles with the remaining shelf life longer than the first preset threshold by:

In an exemplary embodiment of the disclosure, based on the foregoing solution, the daily average sales prediction module 720 obtains historical sales data of the item, and predicts the daily average sales of the item according to the historical sales data by:

In an exemplary embodiment of the disclosure, based on the foregoing solution, the obtaining historical sales data of each target production lot, and predicting the average daily sales of each target production lot corresponding to the article according to the historical sales data of each target production lot includes:

for each of the target production lots, performing the following process:

In an exemplary embodiment of the disclosure, based on the foregoing solution, the target sales cycle determining module 730 determines the target sales cycle of the item according to the current inventory data and the average daily sales volume by:

In an exemplary embodiment of the disclosure, based on the foregoing solution, the aforementioned temporary storage date determination module 740 determines the temporary storage date of the item according to the expiration date of the item and the first preset threshold by:

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the warning information generating apparatus 700 may further include a warning information storage and transmission module configured to:

The specific details of each unit in the above-mentioned warning information generating device have been described in detail in the corresponding warning information generating method, and therefore are not described herein again.

It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.

Moreover, although the steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

In an exemplary embodiment of the present disclosure, there is also provided a computer storage medium capable of implementing the above method. On which a program product capable of implementing the above-described method of the present specification is stored. In some possible embodiments, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to perform the steps according to various exemplary embodiments of the disclosure described in the "exemplary methods" section above of this specification, when the program product is run on the terminal device.

Referring to fig. 8, a program product 800 for implementing the above method according to an embodiment of the present disclosure is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).

In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

As will be appreciated by one skilled in the art, aspects of the present disclosure may be embodied as a system, method or program product. Accordingly, various aspects of the present disclosure may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.

An electronic device 900 according to this embodiment of the disclosure is described below with reference to fig. 9. The electronic device 900 shown in fig. 9 is only an example and should not bring any limitations to the functionality or scope of use of the embodiments of the present disclosure.

As shown in fig. 9, the electronic device 900 is embodied in the form of a general purpose computing device. Components of electronic device 900 may include, but are not limited to: the at least one processing unit 910, the at least one storage unit 920, a bus 930 connecting different system components (including the storage unit 920 and the processing unit 910), and a display unit 940.

Wherein the storage unit stores program code that is executable by the processing unit 910 to cause the processing unit 910 to perform steps according to various exemplary embodiments of the present disclosure described in the above section "exemplary method" of the present specification. For example, the processing unit 910 may perform the following as shown in fig. 1: step S110, obtaining the current inventory data of the articles with the remaining shelf life longer than a first preset threshold; step S120, obtaining historical sales data of the articles, and predicting the daily average sales of the articles according to the historical sales data; step S130, determining a target sale period of the goods according to the current inventory data and the daily average sales volume; step S140, determining the temporary storage date of the article according to the expiration date of the article and the first preset threshold value; and S150, determining the time difference between the temporary storage date and the current date, and generating the early warning information of the articles with the target sale period larger than the time difference. The various steps shown in fig. 2, 4, 5, 6 may also be performed.

The storage unit 920 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM)9201 and/or a cache memory unit 9202, and may further include a read only memory unit (ROM) 9203.

Storage unit 920 may also include a program/utility 9204 having a set (at least one) of program modules 9205, such program modules 9205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.

Bus 930 can be any of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

The electronic device 900 may also communicate with one or more external devices 1000 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 800, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 900 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interface 950. Also, the electronic device 900 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet) via the network adapter 960. As shown, the network adapter 960 communicates with the other modules of the electronic device 900 via the bus 930. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 900, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

Furthermore, the above-described figures are merely schematic illustrations of processes included in methods according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

Claims

1. A method for generating early warning information is characterized by comprising the following steps:

2. The method for generating early warning information according to claim 1, wherein the obtaining of the current inventory data of the articles with the remaining shelf life longer than the first preset threshold comprises:

3. The warning information generating method according to claim 2, wherein the acquiring historical sales data of the item and predicting the average daily sales of the item according to the historical sales data includes:

4. The warning information generating method according to claim 3, wherein the step of obtaining historical sales data of each target production lot, and predicting the average daily sales of each target production lot corresponding to the article according to the historical sales data of each target production lot comprises:

for each of the target production lots, performing the following process:

5. The warning information generating method according to claim 3, wherein the determining a target sale period of the item according to the current inventory data and the average daily sales amount includes:

6. The warning information generation method according to any one of claims 2 to 5, wherein the determining a temporary date of the item according to the expiration date of the item and the first preset threshold includes:

7. The warning information generating method according to claim 6, wherein after generating the warning information of the article whose target sale period is greater than the time difference, the method further comprises:

8. An early warning information generation device, characterized by comprising:

9. A computer-readable storage medium on which a computer program is stored, the program, when executed by a processor, implementing the warning information generating method according to any one of claims 1 to 7.

10. An electronic device, comprising:

one or more processors;

a storage device for storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the warning information generation method of any one of claims 1 to 7.