CN114997970B - Purchasing plan management and control method based on cloud platform and ERP system - Google Patents

Purchasing plan management and control method based on cloud platform and ERP system Download PDF

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CN114997970B
CN114997970B CN202210848332.XA CN202210848332A CN114997970B CN 114997970 B CN114997970 B CN 114997970B CN 202210848332 A CN202210848332 A CN 202210848332A CN 114997970 B CN114997970 B CN 114997970B
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purchase
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CN114997970A (en
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王涛
刘畅
王健国
马宇辉
楼伟杰
吕晓青
胡晓哲
丁宏琳
胡恺锐
吴建锋
吴健超
王婧
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State Grid Zhejiang Zhedian Tendering Consulting Co ltd
State Grid Zhejiang Electric Power Co Ltd
Jinhua Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
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State Grid Zhejiang Electric Power Co Ltd
Jinhua Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
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Abstract

The invention discloses a purchase plan control method based on a cloud platform and an ERP system, which comprises the following steps: s1, a cloud server counts a historical purchase plan, and classifies the types of purchase targets in the historical purchase plan to obtain a first target list and a second target list; s2, the cloud server constructs a standby monitoring table corresponding to the first target list, obtains a first usage value of a first purchase target in a first time period, and calculates a first threshold quantity according to the first time period and the first usage value; s3, generating a current purchasing plan corresponding to the first purchasing target according to a historical purchasing plan, wherein the historical purchasing plan and the current purchasing plan at least comprise purchasing quantity; and S4, the cloud server acquires the purchase request of the request end and generates a current purchase plan corresponding to the second purchase target according to the purchase request.

Description

Purchasing plan management and control method based on cloud platform and ERP system
Technical Field
The invention relates to the technical field of communication, in particular to a purchase plan control method based on a cloud platform and an ERP system.
Background
ERP is a method which is established on the basis of information technology, integrates internal resources and external resources of an enterprise through advanced management ideas and methods, tightly integrates people, properties, objects and the like of the enterprise through standardized data and business operation processes, and finally achieves the purposes of resource optimization configuration and business process optimization.
The purchase can play important supporting role to the normal production of enterprise, life, and the article kind of purchase generally divide into two kinds, including non-continuation demand product and continuation demand product, and non-continuation demand product is in disposable, need not the product of continuation repurchase, for example the printer in the office supplies, and continuation demand product for example with the paper of printer cooperation use.
In the actual use process, different situations may occur for some companies between non-continuous demand products and continuous loss products, and it can be understood that the non-continuous demand products can be products which do not need to be purchased again by a certain company within a time period, and the continuous demand products can be products which need to be purchased again by a certain company within a time period.
The production, the life of continuation demand product to a certain company are more important, so need to keep certain spare capacity and ensure that corresponding company can carry out normal production, and among the prior art, unable according to the difference of article purchase kind, take different purchase plans, so, need a purchase plan management and control system that carries out differentiation purchase according to the purchase target difference urgently.
Disclosure of Invention
The invention overcomes the defects of the prior art, and provides a purchase plan control method based on a cloud platform and an ERP system, which can obtain corresponding purchase plans by adopting different purchase calculation modes according to different article purchase types, so that the purchase plans of different purchase targets are more consistent with corresponding companies.
In order to solve the technical problems, the technical scheme of the invention is as follows:
the embodiment of the invention provides a purchase plan management and control method based on a cloud platform and an ERP system, wherein the ERP system comprises at least one request end, the request end is connected with a cloud server in the cloud platform, and the purchase plan management and control method comprises the following steps:
step S1, a cloud server counts a historical purchasing plan, classifies the types of purchasing targets in the historical purchasing plan to obtain a first target list and a second target list, wherein the first purchasing target in the first target list is a continuous demand product, and the second purchasing target in the second target list is a non-continuous demand product;
s2, the cloud server constructs a standby monitoring table corresponding to the first target list, the standby monitoring table has a first standby quantity of each first purchasing target at the current moment, a first usage value of the first purchasing target in a first time period is obtained, and a first threshold quantity is obtained through calculation according to the first time period and the first usage value;
s3, if the cloud server judges that the first standby number of the first purchasing target in the first target list is smaller than or equal to the first threshold number, generating a current purchasing plan corresponding to the first purchasing target according to a historical purchasing plan, wherein the historical purchasing plan and the current purchasing plan at least comprise purchasing numbers;
and S4, the cloud server acquires a purchase request of a request end, and if a purchase request target in the purchase request corresponds to a second purchase target in a second target list, a current purchase plan corresponding to the second purchase target is generated according to the purchase request.
Further, step S1 includes:
counting all historical purchasing plans, wherein the historical purchasing plans comprise a plurality of historical purchasing information, and each historical purchasing information has corresponding purchasing time, a purchasing target and a purchasing quantity value;
performing primary classification according to the types of the purchasing targets to obtain a first initial list and a second initial list related to all the purchasing targets;
counting the purchasing frequency and the average purchasing quantity of the purchasing targets in each first initial list, and generating a demand evaluation coefficient of the purchasing targets according to the purchasing frequency and the average purchasing quantity of the purchasing targets;
if the demand evaluation coefficient of the purchasing target is smaller than a first preset coefficient, moving the corresponding purchasing target in the first initial list to a second initial list;
when judging that the demand evaluation coefficients of all the purchasing targets in a first initial list are greater than or equal to a first preset coefficient, displaying the first initial list and a second initial list;
and if the determination information of the user is received, taking the first initial list as a first target list, and taking the second initial list as a second target list.
Further, the statistics of the purchase frequency and the average purchase quantity of the purchase target in each first initial list includes:
extracting initial purchasing time and historical purchasing times of each purchasing target in all historical purchasing information, obtaining corresponding purchasing time periods according to the current time and the initial purchasing time, and obtaining corresponding purchasing frequency according to the purchasing time periods and the historical purchasing times;
extracting the purchase quantity of each purchase target in the historical purchase information at each purchase, and obtaining the corresponding average purchase quantity according to the purchase quantity at each purchase and the historical purchase times;
and the first calculation model generates a demand evaluation coefficient of the purchase target according to the purchase frequency and the average purchase quantity of the purchase target.
Further, the generating, by the first calculation model, a demand evaluation coefficient of the purchasing target according to the purchasing frequency and the average purchasing quantity of the purchasing target includes:
the demand evaluation coefficient is calculated by the following formula,
Figure 352739DEST_PATH_IMAGE001
wherein the content of the first and second substances,
Figure 517004DEST_PATH_IMAGE002
is as follows
Figure 617684DEST_PATH_IMAGE003
The demand evaluation coefficient of each procurement target,
Figure 892808DEST_PATH_IMAGE004
is a first
Figure 5120DEST_PATH_IMAGE003
The frequency of purchases by the individual purchase target,
Figure 605866DEST_PATH_IMAGE005
in order to normalize the weight values for the frequencies,
Figure 803629DEST_PATH_IMAGE006
is as follows
Figure 7077DEST_PATH_IMAGE003
The average number of purchases for an individual purchase target,
Figure 505055DEST_PATH_IMAGE007
the weight values are normalized for the number of values,
Figure 745543DEST_PATH_IMAGE008
is a first
Figure 696182DEST_PATH_IMAGE009
The coefficients of the individual procurement objectives calculate the weight values,
Figure 578687DEST_PATH_IMAGE010
is as follows
Figure 665592DEST_PATH_IMAGE003
The current time of each of the procurement objectives,
Figure 201615DEST_PATH_IMAGE011
is a first
Figure 639550DEST_PATH_IMAGE003
The initial procurement time of the individual procurement targets,
Figure 60167DEST_PATH_IMAGE012
is a first
Figure 1578DEST_PATH_IMAGE009
The historical number of purchases for each of the purchase targets,
Figure 115028DEST_PATH_IMAGE013
is a first
Figure 774679DEST_PATH_IMAGE003
Individual procurement objective is
Figure 356577DEST_PATH_IMAGE014
The number of purchases at the time of the second purchase,
Figure 683653DEST_PATH_IMAGE015
is as follows
Figure 702425DEST_PATH_IMAGE003
Upper limit value of purchasing times of each purchasing target.
Further, the method also comprises the following steps:
if the user is judged to adjust the purchasing target in the first initial list to the second initial list;
acquiring a coefficient calculation weight value corresponding to the adjusted purchasing target, reducing the coefficient calculation weight value, subtracting a preset reduction coefficient from the coefficient calculation weight value to obtain a reduced coefficient calculation weight value, wherein each purchasing target has the same coefficient calculation weight value at the initial moment;
if the user is judged to adjust the purchasing target in the second initial list to the first initial list;
and acquiring a coefficient calculation weight value corresponding to the adjusted purchasing target, increasing the coefficient calculation weight value, and adding a preset increasing coefficient to the coefficient calculation weight value to obtain an increased coefficient calculation weight value.
Further, in the step of subtracting a preset reducing coefficient from the coefficient calculation weight value to obtain a reduced coefficient calculation weight value, the reduced coefficient calculation weight value is obtained by the following formula,
Figure 583793DEST_PATH_IMAGE016
wherein the content of the first and second substances,
Figure 611792DEST_PATH_IMAGE017
the weight values are calculated for the reduced coefficients,
Figure 527795DEST_PATH_IMAGE018
setting down the coefficient for the preset value;
in the step of adding the coefficient calculation weight value to a preset heightening coefficient to obtain an heightened coefficient calculation weight value, the heightened coefficient calculation weight value is obtained by the following formula,
Figure 842102DEST_PATH_IMAGE019
wherein, the first and the second end of the pipe are connected with each other,
Figure 741925DEST_PATH_IMAGE020
the weight value is calculated for the increased coefficient,
Figure 42456DEST_PATH_IMAGE021
the coefficient is preset to be increased.
Further, step S2 includes:
the cloud server acquires an initial time corresponding to a first time period, and determines a second standby quantity corresponding to a first purchasing target in a standby monitoring table at the initial time;
obtaining a first usage value according to the difference value between the second standby quantity and the first standby quantity, obtaining an average consumption quantity according to the first time period and the first usage value, and comparing the average consumption quantity with a preset consumption quantity to obtain a consumption trend coefficient;
and performing trend deviation calculation on the standard threshold quantity according to the consumption trend coefficient to obtain a first threshold quantity corresponding to the corresponding first purchasing target.
Further, the performing trend offset calculation on the standard threshold quantity according to the consumption trend coefficient to obtain a first threshold quantity corresponding to the corresponding first purchasing objective includes:
a first threshold quantity corresponding to the first procurement objective is calculated by the following formula,
Figure 812966DEST_PATH_IMAGE022
wherein the content of the first and second substances,
Figure 173540DEST_PATH_IMAGE023
is as follows
Figure 295080DEST_PATH_IMAGE024
A first threshold quantity corresponding to a first procurement objective,
Figure 523936DEST_PATH_IMAGE025
is a first
Figure 414532DEST_PATH_IMAGE024
A second quantity of reserve corresponding to the first procurement objective,
Figure 211586DEST_PATH_IMAGE026
is a first
Figure 554843DEST_PATH_IMAGE024
A first spare amount corresponding to a first procurement objective,
Figure 197177DEST_PATH_IMAGE027
in the first time period,
Figure 207858DEST_PATH_IMAGE028
in order to pre-set the amount of consumption,
Figure 34869DEST_PATH_IMAGE029
in order to trend the offset weight, the weight,
Figure 865422DEST_PATH_IMAGE030
is a first
Figure 577026DEST_PATH_IMAGE024
A standard threshold quantity corresponding to the first procurement objective.
Further, step S3 includes:
when the cloud server judges that the first standby quantity is less than or equal to the first threshold quantity, determining the average purchasing quantity corresponding to the first purchasing target in the historical purchasing plan;
calculating according to the average purchasing quantity and consumption trend coefficient of the first purchasing target to obtain the current purchasing quantity in the current purchasing plan, calculating the current purchasing quantity by the following formula,
Figure 442213DEST_PATH_IMAGE031
wherein, the first and the second end of the pipe are connected with each other,
Figure 315492DEST_PATH_IMAGE032
is as follows
Figure 633340DEST_PATH_IMAGE033
The current purchase quantity for the first purchase target,
Figure 509155DEST_PATH_IMAGE034
is a first
Figure 228849DEST_PATH_IMAGE033
The average number of purchases for the individual first purchase target,
Figure 273028DEST_PATH_IMAGE035
in order to be the consumption tendency coefficient,
Figure 812594DEST_PATH_IMAGE036
is as follows
Figure 725055DEST_PATH_IMAGE033
The number of purchases for the first purchase target is weighted.
Further, the method also comprises the following steps:
displaying the calculated current purchasing quantity, and if receiving the confirmation information, taking the current purchasing quantity as a final current purchasing plan;
if the purchase quantity adjusting information is received, obtaining a final current purchase plan according to the adjusting quantity corresponding to the purchase quantity adjusting information;
and adjusting the calculation weight of the purchasing quantity of the first purchasing target according to the adjusted quantity corresponding to the purchasing quantity adjusting information and the current purchasing quantity.
Further, the adjusting the calculation weight of the purchase quantity of the first purchase target according to the adjustment quantity corresponding to the purchase quantity adjustment information and the current purchase quantity includes:
if the adjustment quantity corresponding to the purchase quantity adjustment information is larger than the current purchase quantity, increasing and adjusting the purchase quantity calculation weight;
if the adjustment quantity corresponding to the purchase quantity adjustment information is smaller than the current purchase quantity, reducing and adjusting the purchase quantity calculation weight;
the increase adjusted and decrease adjusted purchase quantity calculation weights are calculated by the following formula,
Figure 299256DEST_PATH_IMAGE037
wherein, the first and the second end of the pipe are connected with each other,
Figure 514337DEST_PATH_IMAGE038
to increase the weight of the adjusted purchase quantity,Dthe adjustment quantity corresponding to the purchase quantity adjustment information,
Figure 806778DEST_PATH_IMAGE039
the adjustment coefficient is increased, and the adjustment coefficient is increased,
Figure 257351DEST_PATH_IMAGE040
to reduce the weight of the adjusted purchase amount,
Figure 217217DEST_PATH_IMAGE041
to reduce the adjustment factor.
Further, step S4 includes:
if the purchasing request target in the purchasing request corresponds to a second purchasing target in a second target list, extracting the requested purchasing quantity of the second purchasing target in the purchasing request;
and using the requested purchase quantity as the current purchase plan of the second purchase target.
The beneficial effects of the invention are:
(1) The invention provides a purchase plan control method based on a cloud platform and an ERP system, which can classify different purchase targets in a purchase plan and adopt different purchase strategies according to different types of the purchase targets, continuously monitors continuously required products according to a standby monitoring table, and generates a current purchase plan corresponding to a first purchase target when a first standby quantity is less than or equal to a first threshold quantity, so that the invention can realize automatic monitoring on the continuously required products and set a certain standby quantity, a user can obtain stable supply when using the continuously required products, the problem that the company cannot normally produce and live is caused by insufficient supply is avoided, the generation of corresponding purchase plans in different modes according to different types of purchase targets is realized, and the corresponding purchase plans are more in line with the requirements of the corresponding companies;
(2) The method can classify the purchasing targets according to all historical purchasing plans of the request end to obtain a first initial list and a second initial list, in the classifying process, the method can calculate according to dimensions such as purchasing time periods, historical purchasing times, average purchasing quantity and the like of the purchasing targets to obtain corresponding demand evaluation coefficients, the repeated purchasing demand of a company on the corresponding purchasing targets can be embodied through the demand evaluation coefficients, the larger the repeated purchasing demand is, the more likely the corresponding purchasing targets are continuous demand products, and through the mode, the method can obtain the corresponding demand evaluation coefficients according to historical purchasing behaviors of users on the certain purchasing targets, and accurate classification of the purchasing targets is achieved. In addition, the behavior of the user can be monitored, so that the user can adjust the first target list and the second target list according to actual scenes, and the coefficient calculation weight values of different purchasing targets can be adjusted in a differentiation manner according to different adjustments of the user, so that the subsequent requirement evaluation coefficients of the corresponding purchasing targets are more accurate;
(3) When the first threshold value quantity is calculated, the calculation is carried out according to the historical use behaviors of a company, namely the average consumption quantity is obtained according to a first time period and a first use quantity value, a consumption trend coefficient is obtained by combining the comparison of the average consumption quantity and the preset consumption quantity, and the corresponding first threshold value quantity is finally obtained, so that the corresponding purchase targets can be determined according to the consumption behaviors of different types of purchase targets, the first threshold value quantity can be set in a differentiated mode, and the finally formed purchase plan is more in line with the application scene of a user;
(4) When the current purchasing quantity is calculated, the consumption trend coefficient is combined for calculation, if the consumption trend coefficient is larger, the calculated current purchasing quantity is larger, and the purchasing quantity in the next purchasing plan can be obtained according to the consumption. And the invention can combine the purchasing quantity adjustment information of the user to carry out continuous training on the purchasing quantity calculation weight, so that the invention has different and corresponding purchasing quantity calculation weights when calculating different purchasing targets, and consequently, the invention has a more corresponding calculation mode aiming at each purchasing target, and the finally formed purchasing plan is more in line with the use scene of the user.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive labor.
Fig. 1 is a schematic diagram of a system structure of a procurement plan management and control method based on a cloud platform and an ERP system provided by the invention;
fig. 2 is a schematic flow diagram of a first implementation of the method for managing and controlling a procurement plan based on a cloud platform and an ERP system according to the present invention.
Detailed Description
In order that the present invention may be more readily and clearly understood, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings.
The invention provides a purchase plan management and control method based on a cloud platform and an ERP system, as shown in FIG. 1, the ERP system comprises at least one request end, the request end is connected with a cloud server in the cloud platform, the cloud server can be one part of the ERP system, the request ends are multiple, and purchase requests can be sent to the cloud server.
The method provided by the invention performs procurement planning management and control through the following steps, as shown in fig. 2, including:
step S1, the cloud server counts the historical purchasing plan, classifies the types of purchasing targets in the historical purchasing plan, and obtains a first target list and a second target list, wherein the first purchasing target in the first target list is a continuous demand product, and the second purchasing target in the second target list is a non-continuous demand product. The cloud server in the invention can count all historical purchase plans, the historical purchase plan at this time can comprise historical purchase information, and the historical purchase information can be used for purchasing a printer B at the time A, purchasing a printing paper Q box at the time Y and the like. The invention does not limit the purchasing time, the purchasing targets and the purchasing quantity, and the invention classifies the types of the purchasing targets in the historical purchasing plan to obtain a first target list and a second target list.
The continuous demand product can be regarded as a product which is continuously used and lost in the production and life processes of a corresponding company, for example, if a certain company needs to continuously use and consume printing paper in the production and life processes, the printing paper can be regarded as the continuous demand product. The non-continuous demand product can be regarded as a product which is not continuously used and lost in the production and life processes of a corresponding company, for example, a printer, and the printer is not purchased again in a general use scene, so that the printing paper can be regarded as the non-continuous demand product.
In a possible embodiment, the technical solution provided by the present invention, in step S1, includes:
and counting all historical purchasing plans, wherein the historical purchasing plans comprise a plurality of historical purchasing information, and each historical purchasing information has corresponding purchasing time, a purchasing target and a purchasing quantity value. The method and the system can obtain all historical purchasing plans of corresponding companies firstly, the historical purchasing plans can be input by a user in advance, can be directly input to the cloud server, can also be input through a request terminal, and the method and the system do not limit the obtaining mode of the historical purchasing plans. The historical purchasing plan may include a plurality of historical purchasing information, each of which may have a name of a corresponding purchasing target, a purchasing time, and a purchasing quantity value, the name of the purchasing target may be a printer, the purchasing time may be 6 months and 16 days in 2019, and the purchasing quantity value may be 1 station and 2 stations.
And performing primary classification according to the types of the purchasing targets to obtain a first initial list and a second initial list related to all the purchasing targets. The invention firstly classifies once according to the category of the purchasing target and obtains a first initial list and a second initial list corresponding to the category.
In the initial classification, there may be classification performed in various ways. For example, the purchasing targets with the purchasing quantity value greater than or equal to the preset classification quantity value are classified into a first initial list, and the purchasing targets with the purchasing quantity value smaller than the preset classification quantity value are classified into a second initial list. The preset classification magnitude may be 5, 10, etc.
For example, the purchasing targets are classified according to a preset classification table, and the preset classification table has preset names of all preset purchasing targets classified to the first initial list. At this moment, the cloud server classifies the purchasing targets corresponding to the preset names in the historical purchasing information into a first initial list, and classifies the purchasing targets not corresponding to the preset names in the historical purchasing information into a second initial list.
And counting the purchasing frequency and the average purchasing quantity of the purchasing targets in each first initial list, and generating a demand evaluation coefficient of the purchasing targets according to the purchasing frequency and the average purchasing quantity of the purchasing targets. The method and the device can count the purchasing frequency and the average purchasing number of the purchasing targets in the first initial list so as to obtain the corresponding demand evaluation coefficient, the demand of a company for purchasing the corresponding purchasing targets again can be evaluated through the demand evaluation coefficient, and the larger the demand for purchasing the corresponding purchasing targets is, the larger the corresponding demand evaluation coefficient is.
In a possible implementation manner, the counting of the purchasing frequency and the average purchasing number of the purchasing target in each first initial list, and generating the demand evaluation coefficient of the purchasing target according to the purchasing frequency and the average purchasing number of the purchasing target includes:
extracting the initial purchasing time and the historical purchasing times of each purchasing target in all historical purchasing information, obtaining a corresponding purchasing time period according to the current time and the initial purchasing time, and obtaining a corresponding purchasing frequency according to the purchasing time period and the historical purchasing times. For example, one purchasing target corresponds to 3 pieces of historical purchasing information, the purchasing time of the 3 pieces of historical purchasing information is 16 days 6 and 16 months in 2019, 16 days 8 and 16 months in 2019, and 16 days 10 and 16 months in 2019, the initial purchasing time is judged to be 16 days 6 and 16 months in 2019, and the purchasing time period is 4 months from 16 days 6 and 16 months in 2019 to 16 and 16 months in 2019. The corresponding purchasing frequency can be obtained according to the historical purchasing frequency, the purchasing frequency is 3 times, the purchasing frequency can be 3 times divided by 4 months, and the unit time of the frequency is a month.
And extracting the purchasing quantity of each purchasing target in the historical purchasing information at each purchasing time, and obtaining the corresponding average purchasing quantity according to the purchasing quantity at each purchasing time and the historical purchasing times. The method determines the purchasing quantity of each purchasing target in each purchasing, and obtains the corresponding average purchasing quantity, for example, the purchasing quantity of the historical purchasing information with the purchasing time of 2019, 6, 16 days is 10, the purchasing quantity of the historical purchasing information with the purchasing time of 2019, 8, 16 days is 20, and the purchasing quantity of the historical purchasing information with the purchasing time of 2019, 10, 16 days is 30. The present invention will obtain the corresponding average purchase amount, which is 20.
And the first calculation model generates a demand evaluation coefficient of the purchasing target according to the purchasing frequency and the average purchasing quantity of the purchasing target. The method and the device can preset a corresponding first calculation model, and calculate the purchasing frequency and the average purchasing quantity of each purchasing target through the first calculation model to obtain a corresponding demand evaluation coefficient.
In one possible implementation mode, the technical scheme provided by the invention calculates the demand evaluation coefficient through the following formula,
Figure 603199DEST_PATH_IMAGE042
wherein the content of the first and second substances,
Figure 117357DEST_PATH_IMAGE002
is as follows
Figure 246987DEST_PATH_IMAGE003
The demand evaluation coefficient of each procurement target,
Figure 920413DEST_PATH_IMAGE004
is as follows
Figure 742876DEST_PATH_IMAGE003
The frequency of purchases for the individual purchase targets,
Figure 744330DEST_PATH_IMAGE005
in order to normalize the weight values for the frequencies,
Figure 677651DEST_PATH_IMAGE006
is as follows
Figure 346530DEST_PATH_IMAGE003
The average number of purchases for an individual purchase target,
Figure 74314DEST_PATH_IMAGE007
the weight values are normalized for the number of values,
Figure 186233DEST_PATH_IMAGE008
is as follows
Figure 923245DEST_PATH_IMAGE009
The coefficients of the individual procurement goals calculate the weight values,
Figure 181051DEST_PATH_IMAGE010
is as follows
Figure 345316DEST_PATH_IMAGE009
The current time of the individual procurement objective,
Figure 321363DEST_PATH_IMAGE011
is a first
Figure 721120DEST_PATH_IMAGE003
The initial procurement time of the individual procurement targets,
Figure 833432DEST_PATH_IMAGE012
is a first
Figure 434178DEST_PATH_IMAGE009
The historical number of purchases for the individual purchase target,
Figure 631941DEST_PATH_IMAGE043
is as follows
Figure 710756DEST_PATH_IMAGE003
Individual procurement objective is
Figure 802208DEST_PATH_IMAGE014
The number of purchases at the time of the second purchase,
Figure 308276DEST_PATH_IMAGE015
is as follows
Figure 258915DEST_PATH_IMAGE003
Upper limit value of purchasing times of each purchasing target. By passing
Figure 875841DEST_PATH_IMAGE044
Can obtain a purchase time period by
Figure 962745DEST_PATH_IMAGE045
The corresponding purchase frequency is obtained. By passing
Figure 764348DEST_PATH_IMAGE046
The sum of the purchase quantities of all the purchase times can be obtained and passed
Figure 936704DEST_PATH_IMAGE047
The corresponding average purchase quantity is obtained. If the purchasing frequency is larger and the average purchasing quantity is larger, the company is proved to have larger demand for the corresponding purchasing target, and the calculated demand evaluation coefficient is made to be larger. The invention will normalize the weight value by frequency
Figure 622900DEST_PATH_IMAGE048
Quantity normalized weight value
Figure 564311DEST_PATH_IMAGE049
Respectively to purchase frequency
Figure 412181DEST_PATH_IMAGE050
And average purchase quantity
Figure 697931DEST_PATH_IMAGE051
Normalization processing is carried out, finally, weighting calculation is carried out according to the coefficient calculation weight value of each purchase target, and the final demand evaluation coefficient is obtained
Figure 922239DEST_PATH_IMAGE052
。
And if the demand evaluation coefficient of the purchasing target is smaller than a first preset coefficient, moving the corresponding purchasing target in the first initial list to a second initial list. The first preset coefficient which can be 0.1, 1, 10 and the like is preset, and when the demand evaluation coefficient is smaller than the first preset coefficient, the requirement of the company for re-purchasing the corresponding purchasing target is judged to be smaller, so that the corresponding purchasing target in the first initial list is moved to the second initial list.
And when judging that the demand evaluation coefficients of all the purchasing targets in the first initial list are greater than or equal to a first preset coefficient, displaying the first initial list and the second initial list. When the demand evaluation coefficient is larger than or equal to a first preset coefficient, the fact that the demand of the company for repurchasing the corresponding purchasing targets is large is judged, all the purchasing targets in the first initial list are large in demand of repurchasing the company at the moment, the first initial list and the second initial list are displayed at the moment, and the user can check and confirm the purchasing targets.
The method can classify the first initial list and the second initial list in real places according to multiple possible dimensions, then verify the purchasing targets in the first initial list again by combining with the demand evaluation coefficient, and automatically move the purchasing targets with smaller demand evaluation coefficient from the first initial list to the second initial list.
And if the determination information of the user is received, taking the first initial list as a first target list, and taking the second initial list as a second target list. At this time, the user confirms the purchasing targets in the first initial list and the second initial list, that is, the first initial list is used as the first target list, and the second initial list is used as the second target list.
In a possible embodiment, the technical solution provided by the present invention further includes:
if the user is judged to adjust the purchasing target in the first initial list to the second initial list. After the first initial list and the second initial list are displayed for the user, the user may think that some purchasing targets in the first initial list are not greatly worn and needed in the following production and life processes, so the user can actively adjust the purchasing targets in the first initial list to the second initial list at the moment.
And obtaining a coefficient calculation weight value corresponding to the adjusted purchasing target, reducing the coefficient calculation weight value, subtracting a preset reduction coefficient from the coefficient calculation weight value to obtain a reduced coefficient calculation weight value, wherein each purchasing target has the same coefficient calculation weight value at the initial moment. When the user adjusts the corresponding purchasing target from the first initial list to the second initial list, it is proved that the calculated demand evaluation coefficient of the purchasing target is larger, so that the coefficient calculation weight value for calculating the demand evaluation coefficient needs to be reduced at this time, so that the demand evaluation coefficient of the corresponding purchasing target can have a reduced trend when being calculated next time, and the calculated demand evaluation coefficient of the corresponding purchasing target is more consistent with the calculation scene of the current user.
If the user is judged to adjust the purchasing target in the second target list to the first initial list. The user may think that some purchasing targets in the second initial list are more worn and needed in the following production and life processes, so the user can actively adjust the purchasing targets in the second initial list to the first initial list at this time.
And acquiring a coefficient calculation weight value corresponding to the adjusted purchasing target, carrying out height adjustment processing on the coefficient calculation weight value, and adding a preset height adjustment coefficient to the coefficient calculation weight value to obtain the increased coefficient calculation weight value. When the user adjusts the corresponding purchasing objective from the first initial list to the first initial list, it is proved that the calculated demand evaluation coefficient of the purchasing objective is smaller, so that the coefficient calculation weight value for calculating the demand evaluation coefficient needs to be increased at this time, so that the demand evaluation coefficient of the corresponding purchasing objective can have an increasing trend when the demand evaluation coefficient of the corresponding purchasing objective is calculated next time, and the calculated demand evaluation coefficient of the corresponding purchasing objective better conforms to the calculation scene of the current user.
It should be noted that, in the calculation scenario of the present invention, each purchasing target has the same coefficient calculation weight value at the initial time, and through the above technical solution, the coefficient calculation weight value of each purchasing target can be continuously adjusted and trained, so that the subsequent calculation of the demand evaluation coefficient of each purchasing target is more accurate.
In a possible embodiment, in the step of subtracting a preset reducing coefficient from the coefficient calculation weight value to obtain a reduced coefficient calculation weight value, the reduced coefficient calculation weight value is obtained by the following formula,
Figure 983736DEST_PATH_IMAGE016
wherein the content of the first and second substances,
Figure 736929DEST_PATH_IMAGE017
the weight values are calculated for the reduced coefficients,
Figure 883876DEST_PATH_IMAGE018
the coefficient is turned down for a preset value.
The preset reducing coefficient is preset, when the coefficient calculation weight value is judged to be required to be reduced, the coefficient calculation weight value is reduced by the preset reducing coefficient, the preset reducing coefficient can be 0.1, 0.2 and the like, the specific numerical value of the preset reducing coefficient is not limited, the preset reducing coefficient is required to be smaller than the coefficient calculation weight value, and the situation that the preset reducing coefficient is required to be smaller than the coefficient calculation weight value is avoided
Figure 911875DEST_PATH_IMAGE053
A situation less than 0 occurs. By the method, the reduced coefficient calculation weight value can be obtained
Figure 952512DEST_PATH_IMAGE017
。
In the step of adding the coefficient calculation weight value to a preset heightening coefficient to obtain a heightened coefficient calculation weight value, the heightened coefficient calculation weight value is obtained by the following formula,
Figure 142185DEST_PATH_IMAGE054
wherein the content of the first and second substances,
Figure 510850DEST_PATH_IMAGE020
the weight value is calculated for the increased coefficient,
Figure 76960DEST_PATH_IMAGE055
is a preset turn-up factor.
The preset heightening coefficient is preset, when the coefficient calculation weight value is required to be heightened, the preset heightening coefficient is added to the coefficient calculation weight value, the preset heightening coefficient can be 0.1, 0.2 and the like, and the specific numerical value of the preset heightening coefficient is not limited. By the method, the increased coefficient calculation weight value can be obtained
Figure 113049DEST_PATH_IMAGE056
。
S2, the cloud server constructs a standby monitoring table corresponding to the first target list, the standby monitoring table has a first standby quantity of each first purchasing target at the current moment, a first usage value of the first purchasing target in a first time period is obtained, and a first threshold quantity is obtained through calculation according to the first time period and the first usage value. In the actual production and living process of a company, standby setting is carried out on required articles and equipment with losses, so that the standby monitoring table can be preset, and the standby monitoring table at the moment mainly monitors the standby quantity of a first purchasing target in a first target list. The invention obtains a first usage value of a first procurement target in a first time period, and the first usage value can be regarded as the usage amount of printing paper, ink cartridges and the like in a month. The method integrates the first time period and the first usage value to calculate the first threshold quantity, the first threshold quantity can be regarded as the lowest quantity allowed to be reserved by the corresponding first purchasing target, and when the first standby quantity of the first purchasing target is smaller than the first threshold quantity, the corresponding standby quantity of the first purchasing target is proved to be less at the moment, so that the normal production and life of a company can be influenced, and corresponding processing is needed at the moment.
In a possible implementation manner, the technical solution provided by the present invention, step S2 includes:
the cloud server obtains an initial time corresponding to the first time period, and determines a second standby quantity corresponding to the initial time of the first purchasing target in the standby monitoring table. For example, the first time period is from 2019, month and 16 days 9, month and 16 days 2019, month and 16 days 10, month and 16 days, the starting time at this time is 2019, month and 16 days 9, and for example, the number of the first procurement targets corresponding to the 2019, month and 16 days 9 is 10 boxes, and the second standby number at this time is 10 boxes. At the present moment, for example, 10, month and 16 days in 2019, the corresponding first procurement target quantity is 5 boxes, and the first standby quantity at the present moment is 5 boxes.
And obtaining a first usage value according to the difference value between the second standby quantity and the first standby quantity, obtaining an average consumption quantity according to the first time period and the first usage value, and comparing the average consumption quantity with a preset consumption quantity to obtain a consumption trend coefficient. The first usage value at this time is 10 boxes minus 5 boxes to 5 boxes, that is, the first usage value for the first procurement target in the range from 16 days 9 and 16 months 2019 to 16 days 10 and 16 months 2019 is 5 boxes. At this time, the present invention will obtain the corresponding average consumption amount, i.e. 5 boxes/month, which is the time unit of month. At this time, the present invention may preset a preset consumption amount, for example, the preset consumption amount is 3 boxes/month, and the preset consumption amount may be set by comprehensive evaluation performed by a user in a conventional production and life of a company.
And performing trend offset calculation on the standard threshold quantity according to the consumption trend coefficient to obtain a first threshold quantity corresponding to the corresponding first purchasing target. The trend deviation calculation is carried out on the standard threshold quantity according to the consumption trend coefficient, it needs to be noted that the deviation can be positive deviation or negative deviation, the use requirement of a recent company on a corresponding first purchasing target can be reflected through the consumption trend coefficient, and if the use requirement is larger, the consumption trend coefficient is larger. Conversely, if the demand for use is smaller, the consumption tendency coefficient is smaller. The consumption trend coefficient is larger when the combined use requirement is larger, the final first threshold number is obtained, the first threshold number can be regarded as the minimum safety quantity of the stock, and when the first standby number of the first purchasing target is lower than the first threshold number, the first purchasing target is proved to be less at the moment, and the normal production and life of a company can be influenced. Through the mode, different using requirements of different first purchasing targets of the invention are subjected to differential calculation to obtain the first threshold quantity which is differential and suitable for the corresponding company.
In a possible implementation manner, the performing trend offset calculation on the standard threshold number according to the consumption trend coefficient to obtain a first threshold number corresponding to a corresponding first purchasing objective includes:
a first threshold amount corresponding to the first procurement objective is calculated by the following equation,
Figure 598257DEST_PATH_IMAGE057
wherein the content of the first and second substances,
Figure 454218DEST_PATH_IMAGE023
is a first
Figure 824019DEST_PATH_IMAGE024
A first threshold quantity corresponding to a first procurement objective,
Figure 714615DEST_PATH_IMAGE058
is a first
Figure 246090DEST_PATH_IMAGE024
A second spare amount corresponding to the first procurement objective,
Figure 713981DEST_PATH_IMAGE026
is as follows
Figure 621894DEST_PATH_IMAGE024
A first spare amount corresponding to a first procurement objective,
Figure 366996DEST_PATH_IMAGE059
in the first time period,
Figure 69373DEST_PATH_IMAGE028
in order to pre-set the amount of consumption,
Figure 165505DEST_PATH_IMAGE029
in order to trend the offset weight, the weight,
Figure 611530DEST_PATH_IMAGE030
is as follows
Figure 834307DEST_PATH_IMAGE024
A standard threshold quantity corresponding to the first procurement objective. By passing
Figure 707585DEST_PATH_IMAGE060
The consumption trend coefficient can be calculated in
Figure 25434DEST_PATH_IMAGE061
The greater the standard threshold quantity corresponding to the first procurement objective is, the greater the deviation is, the greater the first threshold quantity calculated at that time
Figure 540729DEST_PATH_IMAGE023
The larger, if
Figure 994844DEST_PATH_IMAGE062
Is a negative number, then
Figure 163657DEST_PATH_IMAGE063
The smaller the first threshold number calculated at that time
Figure 234381DEST_PATH_IMAGE023
The smaller.
And S3, if the cloud server judges that the first standby number of the first purchasing target in the first target list is smaller than or equal to the first threshold number, generating a current purchasing plan corresponding to the first purchasing target according to the historical purchasing plan, wherein the historical purchasing plan and the current purchasing plan at least comprise purchasing numbers. The cloud server may monitor and detect a first spare quantity of a first purchase target in a first target list in real time at regular time, and respond when the first spare quantity is smaller than or equal to a first threshold quantity. It should be noted that the first standby quantity of the first procurement target may be uploaded by a worker according to actual use or uploaded by a warehouse manager, and in some scenarios, the corresponding first standby quantity may be obtained according to automatic statistics of warehousing and warehousing behaviors and ex-warehouse behaviors performed by an ex-warehouse system.
When the first spare quantity is less than or equal to the first threshold quantity, the spare quantity of the equipment and the articles corresponding to the first purchasing target which are frequently used at the moment is proved to be less, and the normal operation of a follow-up company can be influenced, so that the current purchasing plan corresponding to the first purchasing target can be generated according to the historical purchasing plan at the moment, and the current purchasing behavior can be determined by combining the historical purchasing behavior through the mode, so that the purchasing quantity in the current purchasing plan is more in line with the purchasing requirement and the purchasing rule of a corresponding user.
In a possible implementation manner, the technical solution provided by the present invention, in step S3, includes:
when the cloud server judges that the first standby quantity is smaller than or equal to the first threshold quantity, the cloud server determines the average purchasing quantity corresponding to the first purchasing target in the historical purchasing plan. At this time, it is determined that the corresponding purchase is required for the first purchase target, and the present invention obtains the corresponding average purchase amount in the historical purchase plan.
Calculating according to the average purchasing quantity and consumption trend coefficient of the first purchasing target to obtain the current purchasing quantity in the current purchasing plan, calculating the current purchasing quantity by the following formula,
Figure 22209DEST_PATH_IMAGE064
wherein, the first and the second end of the pipe are connected with each other,
Figure 596410DEST_PATH_IMAGE065
is a first
Figure 811490DEST_PATH_IMAGE033
The current number of purchases for the first purchase target,
Figure 369511DEST_PATH_IMAGE034
is as follows
Figure 820084DEST_PATH_IMAGE033
The average number of purchases for the individual first purchase target,
Figure 248791DEST_PATH_IMAGE066
in order to be the consumption tendency coefficient,
Figure 900352DEST_PATH_IMAGE036
is as follows
Figure 414510DEST_PATH_IMAGE033
The number of purchases for the first purchase target is weighted.
First, the
Figure 809719DEST_PATH_IMAGE033
Average number of purchases of first purchase target and second purchase target
Figure 483146DEST_PATH_IMAGE003
The average number of purchases for each purchase target may be the same, i.e., the average number of purchases for the first purchase target may be obtained by dividing the total number of purchases over the corresponding time period by the length of the time period, and for the second purchase target
Figure 40029DEST_PATH_IMAGE033
The average purchase quantity of the first purchase target is not described in detail in the present invention.
Figure 41483DEST_PATH_IMAGE067
In (1)
Figure 240384DEST_PATH_IMAGE025
Is a first
Figure 643683DEST_PATH_IMAGE033
A second spare amount corresponding to the first procurement objective,
Figure 997566DEST_PATH_IMAGE026
is as follows
Figure 486317DEST_PATH_IMAGE033
A first spare quantity corresponding to the first procurement objective. By passing
Figure 957749DEST_PATH_IMAGE068
Can be calculated to obtain
Figure 481134DEST_PATH_IMAGE033
A consumption trend coefficient corresponding to the first procurement objective. If the consumption trend coefficient is larger, the consumption speed of the corresponding first purchasing target in the using process is proved to be higher, so that the current purchasing number of the first purchasing target needs to be increased at the moment. If the consumption trend coefficient is smaller, the consumption speed of the corresponding first purchasing target in the using process is proved to be slower, so that the current purchasing number of the first purchasing target needs to be reduced at the moment. Calculating weight of purchase quantity of first purchase target
Figure 504454DEST_PATH_IMAGE036
May be preset.
In a possible embodiment, the technical solution provided by the present invention further includes:
and displaying the calculated current purchasing quantity, and if confirmation information is received, taking the current purchasing quantity as a final current purchasing plan. The invention displays the user after obtaining the current purchasing quantity, if the user inputs the confirmation information, the user considers that the calculated quantity is suitable for the current use scene, and the calculated current purchasing quantity is taken as the final current purchasing plan, namely, the first purchasing target is purchased according to the current purchasing quantity.
And if the purchase quantity adjusting information is received, obtaining a final current purchase plan according to the adjustment quantity corresponding to the purchase quantity adjusting information. Then the user considers that the calculated current purchasing quantity may not particularly meet the purchasing requirement and purchasing scenario of the company, so that the current purchasing quantity needs to be adjusted at this time, that is, the adjusted quantity is used as the final current purchasing plan.
Through the technical scheme, the invention can automatically calculate the current purchasing quantity, continuously revise and correct the current purchasing quantity according to the user, improve the efficiency of the user in determining the current purchasing plans of various first purchasing targets and ensure the corresponding accuracy of the current purchasing plans.
And adjusting the calculation weight of the purchasing quantity of the first purchasing target according to the adjusted quantity corresponding to the purchasing quantity adjusting information and the current purchasing quantity. After receiving the purchase quantity adjusting information of a certain first purchase target, the invention can calculate the weight according to the purchase quantity to adjust, so that the purchase quantity calculation weight is more in line with the calculation scene of a corresponding company, and the accuracy of the current purchase quantity calculated by the subsequent corresponding first purchase target is ensured.
In a possible embodiment, the adjusting the calculation weight of the purchase quantity of the first purchase target according to the adjusted quantity corresponding to the purchase quantity adjustment information and the current purchase quantity includes:
if the adjustment quantity corresponding to the purchase quantity adjustment information is larger than the current purchase quantity, increasing and adjusting the purchase quantity calculation weight;
if the adjustment quantity corresponding to the purchase quantity adjustment information is smaller than the current purchase quantity, reducing and adjusting the purchase quantity calculation weight;
the increase adjusted and decrease adjusted purchase quantity calculation weights are calculated by the following formula,
Figure 480500DEST_PATH_IMAGE069
wherein the content of the first and second substances,
Figure 490045DEST_PATH_IMAGE070
to increase the weight of the adjusted purchase amount,
Figure 867936DEST_PATH_IMAGE071
adjusting the adjusted quantity corresponding to the information for the purchase quantity,
Figure 62157DEST_PATH_IMAGE072
the adjustment coefficient is increased and the adjustment coefficient is increased,
Figure 525500DEST_PATH_IMAGE040
to reduce the weight of the adjusted purchase amount,
Figure 604314DEST_PATH_IMAGE041
to reduce the adjustment factor. By passing
Figure 836712DEST_PATH_IMAGE073
Can be calculated to obtain the amplitude of the weight increase adjustment of the purchase quantity calculation,
Figure 342780DEST_PATH_IMAGE074
the larger the purchase quantity calculation weight increase adjustment, the larger the magnitude. By passing
Figure 152473DEST_PATH_IMAGE075
Calculation can be performed to obtain the magnitude of the weight reduction adjustment for the purchase quantity calculation,
Figure 34978DEST_PATH_IMAGE076
the greater the magnitude of the purchase quantity calculation weight reduction adjustment. The invention can calculate the purchase quantity according to the error between the current purchase quantity and the adjustment quantityThe weight is calculated and adjusted, so that the adjusted purchase quantity calculation weight is more accurate and is suitable for the current calculation scene.
And S4, the cloud server acquires a purchase request of a request end, and if a purchase request target in the purchase request corresponds to a second purchase target in a second target list, a current purchase plan corresponding to the second purchase target is generated according to the purchase request. The cloud server also receives a purchase request of the request end, and in general, the request end sends the purchase request to the cloud server only on the premise that corresponding standby products and equipment are not provided, and if a purchase request target in the purchase request corresponds to a second purchase target in a second target list, the second purchase target is proved not to be a continuously used and worn article, so that the current purchase plan corresponding to the second purchase target can be directly generated according to the purchase request.
In a possible implementation manner, the technical solution provided by the present invention, in step S4, includes:
and if the purchasing request target in the purchasing request corresponds to a second purchasing target in a second target list, extracting the requested purchasing quantity of the second purchasing target in the purchasing request. Typically, the purchase request includes a requested purchase amount, e.g., 1 or 2, corresponding to the second purchase target. The second procurement target at this time may be a printer.
And using the requested purchasing quantity as the current purchasing plan of the second purchasing target. The invention takes the requested purchase quantity uploaded by the request terminal as the current purchase plan of the second purchase target.
Through the mode, different purchasing plans are adopted according to different types of purchasing targets, so that normal production and life of corresponding companies can be guaranteed, and the generation efficiency of the purchasing plans is improved.
In addition to the above embodiments, the present invention may have other embodiments; all technical solutions formed by adopting equivalent substitutions or equivalent transformations fall within the protection scope of the present invention.

Claims (7)

1. The method for managing and controlling the purchase plan based on the cloud platform and the ERP system is characterized in that the ERP system comprises at least one request end, the request end is connected with a cloud server in the cloud platform, and the purchase plan is managed and controlled through the following steps of:
step S1, a cloud server counts a historical purchasing plan, classifies the types of purchasing targets in the historical purchasing plan to obtain a first target list and a second target list, wherein the first purchasing target in the first target list is a continuous demand product, and the second purchasing target in the second target list is a non-continuous demand product;
s2, the cloud server constructs a standby monitoring table corresponding to the first target list, wherein the standby monitoring table has a first standby quantity of each first purchasing target at the current moment, a first usage value of the first purchasing target in a first time period is obtained, and a first threshold quantity is obtained through calculation according to the first time period and the first usage value;
step S3, if the cloud server judges that the first standby quantity of the first purchasing target in the first target list is smaller than or equal to the first threshold quantity, generating a current purchasing plan corresponding to the first purchasing target according to a historical purchasing plan, wherein the historical purchasing plan and the current purchasing plan at least comprise purchasing quantities;
s4, the cloud server acquires a purchase request of a request end, and if a purchase request target in the purchase request corresponds to a second purchase target in a second target list, a current purchase plan corresponding to the second purchase target is generated according to the purchase request;
the step S1 comprises the following steps:
counting all historical purchasing plans, wherein the historical purchasing plans comprise a plurality of historical purchasing information, and each historical purchasing information has corresponding purchasing time, a purchasing target and a purchasing quantity value;
performing primary classification according to the types of the purchasing targets to obtain a first initial list and a second initial list related to all the purchasing targets;
counting the purchasing frequency and the average purchasing quantity of the purchasing targets in each first initial list, and generating a demand evaluation coefficient of the purchasing targets according to the purchasing frequency and the average purchasing quantity of the purchasing targets;
if the demand evaluation coefficient of the purchasing target is smaller than a first preset coefficient, moving the corresponding purchasing target in the first initial list to a second initial list;
when the demand evaluation coefficients of all the purchasing targets in the first initial list are judged to be more than or equal to a first preset coefficient, displaying the first initial list and the second initial list;
if the determination information of the user is received, taking the first initial list as a first target list, and taking the second initial list as a second target list;
the counting of the purchasing frequency and the average purchasing number of the purchasing targets in each first initial list and the generation of the demand evaluation coefficient of the purchasing targets according to the purchasing frequency and the average purchasing number of the purchasing targets comprise:
extracting initial purchasing time and historical purchasing times of each purchasing target in all historical purchasing information, obtaining corresponding purchasing time periods according to the current time and the initial purchasing time, and obtaining corresponding purchasing frequency according to the purchasing time periods and the historical purchasing times;
extracting the purchase quantity of each purchase target in the historical purchase information at each purchase, and obtaining the corresponding average purchase quantity according to the purchase quantity at each purchase and the historical purchase times;
the first calculation model generates a demand evaluation coefficient of the purchasing target according to the purchasing frequency and the average purchasing quantity of the purchasing target;
the first calculation model generates a demand evaluation coefficient of the procurement target according to the procurement frequency and the average procurement quantity of the procurement target, and includes:
the demand evaluation coefficient is calculated by the following formula,
Figure 267788DEST_PATH_IMAGE002
wherein, the first and the second end of the pipe are connected with each other,
Figure DEST_PATH_IMAGE003
is as follows
Figure 6812DEST_PATH_IMAGE004
The demand evaluation coefficient of each procurement target,
Figure DEST_PATH_IMAGE005
is as follows
Figure 567237DEST_PATH_IMAGE004
The frequency of purchases for the individual purchase targets,
Figure 715322DEST_PATH_IMAGE006
the weight values are normalized for the frequency and,
Figure DEST_PATH_IMAGE007
is as follows
Figure 904689DEST_PATH_IMAGE004
The average number of purchases for an individual purchase target,
Figure 50500DEST_PATH_IMAGE008
the weight values are normalized for the number of values,
Figure DEST_PATH_IMAGE009
is as follows
Figure 160538DEST_PATH_IMAGE004
The coefficients of the individual procurement goals calculate the weight values,
Figure 784418DEST_PATH_IMAGE010
is as follows
Figure 224364DEST_PATH_IMAGE004
The current time of the individual procurement objective,
Figure DEST_PATH_IMAGE011
is as follows
Figure 682021DEST_PATH_IMAGE004
The initial procurement time of each procurement target,
Figure 872831DEST_PATH_IMAGE012
is as follows
Figure 503664DEST_PATH_IMAGE004
The historical number of purchases for each of the purchase targets,
Figure DEST_PATH_IMAGE013
is as follows
Figure 204642DEST_PATH_IMAGE004
Individual procurement objective is
Figure 754572DEST_PATH_IMAGE014
The number of purchases at the time of the sub-purchase,
Figure DEST_PATH_IMAGE015
is a first
Figure 776885DEST_PATH_IMAGE004
The upper limit value of the purchasing times of each purchasing target;
further comprising:
if the user is judged to adjust the purchasing target in the first initial list to the second initial list;
acquiring a coefficient calculation weight value corresponding to the adjusted purchasing target, reducing the coefficient calculation weight value, subtracting a preset reduction coefficient from the coefficient calculation weight value to obtain a reduced coefficient calculation weight value, wherein each purchasing target has the same coefficient calculation weight value at the initial moment;
if the user is judged to adjust the purchasing target in the second initial list to the first initial list;
acquiring a coefficient calculation weight value corresponding to the adjusted purchasing target, carrying out heightening processing on the coefficient calculation weight value, and adding a preset heightening coefficient to the coefficient calculation weight value to obtain an heightened coefficient calculation weight value;
in the step of subtracting a preset lowering coefficient from the coefficient calculation weight value to obtain a lowered coefficient calculation weight value, the lowered coefficient calculation weight value is obtained by the following formula,
Figure DEST_PATH_IMAGE017
wherein, the first and the second end of the pipe are connected with each other,
Figure 772261DEST_PATH_IMAGE018
the weight values are calculated for the reduced coefficients,
Figure DEST_PATH_IMAGE019
a preset turn down factor;
in the step of adding the coefficient calculation weight value to a preset heightening coefficient to obtain a heightened coefficient calculation weight value, the heightened coefficient calculation weight value is obtained by the following formula,
Figure DEST_PATH_IMAGE021
wherein the content of the first and second substances,
Figure 563631DEST_PATH_IMAGE022
the weight value is calculated for the increased coefficient,
Figure DEST_PATH_IMAGE023
the coefficient is preset to be increased.
2. The cloud platform and ERP system based purchasing plan management and control method as claimed in claim 1, wherein the step S2 comprises:
the cloud server acquires an initial time corresponding to a first time period, and determines a second standby quantity corresponding to a first purchase target in a standby monitoring table at the initial time;
obtaining a first usage value according to the difference value between the second standby quantity and the first standby quantity, obtaining an average consumption quantity according to the first time period and the first usage value, and comparing the average consumption quantity with a preset consumption quantity to obtain a consumption trend coefficient;
and performing trend offset calculation on the standard threshold quantity according to the consumption trend coefficient to obtain a first threshold quantity corresponding to the corresponding first purchasing target.
3. The cloud platform and ERP system-based procurement plan control method of claim 2,
performing trend offset calculation on the standard threshold quantity according to the consumption trend coefficient to obtain a first threshold quantity corresponding to a corresponding first purchasing target, including:
a first threshold amount corresponding to the first procurement objective is calculated by the following equation,
Figure DEST_PATH_IMAGE025
wherein, the first and the second end of the pipe are connected with each other,
Figure 805168DEST_PATH_IMAGE026
is a first
Figure DEST_PATH_IMAGE027
A first threshold quantity corresponding to a first procurement objective,
Figure 377095DEST_PATH_IMAGE028
is a first
Figure 146468DEST_PATH_IMAGE027
A second quantity of reserve corresponding to the first procurement objective,
Figure DEST_PATH_IMAGE029
is a first
Figure 149934DEST_PATH_IMAGE027
A first spare amount corresponding to a first procurement objective,
Figure 713770DEST_PATH_IMAGE030
in order to be the first period of time,
Figure DEST_PATH_IMAGE031
in order to pre-set the amount of consumption,
Figure 772993DEST_PATH_IMAGE032
in order to trend the offset weights,
Figure DEST_PATH_IMAGE033
is as follows
Figure 985537DEST_PATH_IMAGE027
A standard threshold quantity corresponding to the first procurement objective.
4. The cloud platform and ERP system-based procurement plan management and control method according to claim 3, wherein step S3 comprises:
when the cloud server judges that the first standby quantity is less than or equal to the first threshold quantity, determining the average purchasing quantity corresponding to the first purchasing target in the historical purchasing plan;
calculating according to the average purchasing quantity and consumption trend coefficient of the first purchasing target to obtain the current purchasing quantity in the current purchasing plan, calculating the current purchasing quantity by the following formula,
Figure DEST_PATH_IMAGE035
wherein the content of the first and second substances,
Figure 344974DEST_PATH_IMAGE036
is a first
Figure DEST_PATH_IMAGE037
The current purchase quantity for the first purchase target,
Figure 486237DEST_PATH_IMAGE038
is a first
Figure 796870DEST_PATH_IMAGE037
The average number of purchases for the first purchase target,
Figure DEST_PATH_IMAGE039
in order to be a coefficient of the consumption tendency,
Figure 439204DEST_PATH_IMAGE040
is as follows
Figure 590831DEST_PATH_IMAGE037
The number of purchases for the first purchase target is weighted.
5. The cloud platform and ERP system-based procurement plan management and control method of claim 4, further comprising:
displaying the calculated current purchasing quantity, and if receiving the confirmation information, taking the current purchasing quantity as a final current purchasing plan;
if the purchase quantity adjusting information is received, obtaining a final current purchase plan according to the adjusting quantity corresponding to the purchase quantity adjusting information;
and adjusting the calculation weight of the purchasing quantity of the first purchasing target according to the adjusted quantity corresponding to the purchasing quantity adjusting information and the current purchasing quantity.
6. The cloud platform and ERP system-based procurement plan management and control method of claim 5,
the adjusting of the calculation weight of the purchasing quantity of the first purchasing target according to the adjusting quantity corresponding to the purchasing quantity adjusting information and the current purchasing quantity comprises the following steps:
if the adjustment quantity corresponding to the purchase quantity adjustment information is larger than the current purchase quantity, increasing and adjusting the purchase quantity calculation weight;
if the adjustment quantity corresponding to the purchase quantity adjustment information is smaller than the current purchase quantity, reducing and adjusting the purchase quantity calculation weight;
the increase adjusted and decrease adjusted purchase quantity calculation weights are calculated by the following formula,
Figure DEST_PATH_IMAGE041
wherein the content of the first and second substances,
Figure 27629DEST_PATH_IMAGE042
to increase the weight of the adjusted purchase amount,
Figure DEST_PATH_IMAGE043
the adjustment quantity corresponding to the purchase quantity adjustment information,
Figure 780819DEST_PATH_IMAGE044
in order to increase the adjustment factor,
Figure DEST_PATH_IMAGE045
to reduce the weight of the adjusted purchase quantity,
Figure 164527DEST_PATH_IMAGE046
to reduce the adjustment factor.
7. The cloud platform and ERP system based purchasing plan management and control method as claimed in claim 1, wherein the step S4 comprises:
if the purchasing request target in the purchasing request corresponds to a second purchasing target in a second target list, extracting the requested purchasing quantity of the second purchasing target in the purchasing request;
and using the requested purchasing quantity as the current purchasing plan of the second purchasing target.
CN202210848332.XA 2022-07-19 2022-07-19 Purchasing plan management and control method based on cloud platform and ERP system Active CN114997970B (en)

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