CN112418771B - Distribution system of food packaging film - Google Patents
Distribution system of food packaging film Download PDFInfo
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- CN112418771B CN112418771B CN202011444063.8A CN202011444063A CN112418771B CN 112418771 B CN112418771 B CN 112418771B CN 202011444063 A CN202011444063 A CN 202011444063A CN 112418771 B CN112418771 B CN 112418771B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
- G06Q10/0832—Special goods or special handling procedures, e.g. handling of hazardous or fragile goods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
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- G06Q30/00—Commerce
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Abstract
The invention discloses a distribution system of a food packaging film, relates to the technical field of distribution of packaging films, and solves the technical problems of high labor cost and low distribution efficiency in the distribution order processing process; the invention is provided with the data analysis module, and the data analysis module can ensure that the order is processed in time and is beneficial to arranging the production plan of the production workshop; the logistics scheduling module is arranged, and the reservation information is sent to the server of the logistics company according to the demand and the delivery address to reserve the transport vehicles and check the logistics, so that the delivery efficiency of the food packaging film is improved, and the labor cost is reduced; the invention designs the distribution system of the food packaging film, can ensure the reliability of distributors and the accuracy of logistics distribution, can also predict the future demand, can reasonably arrange the production time and reduce the cost.
Description
Technical Field
The invention belongs to the field of packaging film distribution, relates to an intelligent distribution technology, and particularly relates to a distribution system of a food packaging film.
Background
The food packaging film is a high polymer material which is used for wrapping the surface of food and is mainly used for isolating and decomposing the entering of microorganism bacteria and external pollutants and preventing and prolonging the deterioration of the food; there are many types of food packaging films, such as photocatalytic inorganic antibacterial agent films, natural and polymeric antibacterial agent films, inorganic antibacterial agent films, composite antibacterial agent films, and organic antibacterial agent films.
The food packaging film is used for various aspects in daily life, and the consumption is particularly high; however, the distribution process of the food packaging film is incomplete, the order quantity of the merchants is not updated timely, the logistics take-over cannot arrange transportation in advance, and distributors cannot acquire the food packaging film timely, so that a distribution system of the food packaging film is urgently needed.
Disclosure of Invention
In order to solve the problems of the scheme, the invention provides a distribution system of food packaging films.
The purpose of the invention can be realized by the following technical scheme: a distribution system of food packaging films comprises a processor, a credit analysis module, a management scheduling module, a data storage module, a user registration module, a data analysis module and a logistics scheduling module;
the user registration module is used for registering the distributor and analyzing the registration information of the distributor;
the data analysis module is used for screening current order information and predicting future order information; the data analysis module comprises a current order analysis unit and a future order prediction unit;
the logistics scheduling module places an order according to the order information to obtain a logistics demand and sends the logistics demand to a logistics company; the logistics scheduling module is in communication connection with a server of a logistics company;
the credit analysis module is used for analyzing the credit of the distributor to obtain an analysis result and screening the distributor according to the analysis result.
Preferably, the distributor registers through the user registration module, including:
the distributor sends verification information to the user registration module through the intelligent terminal; the intelligent terminal comprises an intelligent mobile phone, a tablet computer and a notebook computer, and is in communication connection with the user registration module; the verification information comprises a business license, a legal representative, a mobile phone number of a legal person, a business address, a business range and a business period;
the processor identifies the authenticity of the business license, and when the business license is identified as authentic, the business range is analyzed; when the business license is identified as false, sending a business license abnormal signal to the intelligent terminal of the distributor;
acquiring a preset business range stored in a data storage module through a processor; the preset business range is a business range allowing a distributor to engage in food packaging film wholesale business;
matching the business range with a preset range, and judging that the business range meets the requirement when the matching is successful; when the matching fails, sending a business range abnormal signal to an intelligent terminal of the distributor;
and marking the distributor with the business range meeting the requirement as a qualified distributor, and sending the verification information of the qualified distributor to the data storage module for storage through the processor.
Preferably, the data analysis module is configured to analyze current order information and predict future orders, and includes:
the processor marks the received order information as current order information and sends the current order information to the current order analysis unit;
the current order analysis unit acquires the demand, the distribution address and the demand time in the current order after receiving the current order information;
acquiring a business address of a distributor corresponding to the current order information through a data storage module; matching the distribution address with the business address, and analyzing the demand when the matching is successful; when the matching fails, an address confirmation signal is sent to the distributor; the distributor confirms the address after receiving the address confirmation signal, sends the address confirmation signal to the current order analysis unit after the address confirmation is successful, and the order analysis unit analyzes the demand after receiving the address confirmation signal;
acquiring a time difference value between the required time and the current time in real time, and marking the time difference value as SC;
when the time difference SC meets SC < L1, judging that the current order can not finish delivery at the specified time, and sending a time exception signal to the distributor through the processor; when the time difference SC is equal to or larger than SC 1, acquiring the stock quantity, and marking the stock quantity as KL; wherein L1 is a preset time difference threshold, and L1 is a real number greater than 0;
winning the daily output of the production workshop, and marking the daily output and the demand as RL and XQ respectively;
acquiring a supply quantity GL by a formula GL ═ KL + RL × (SC-L2); wherein L2 is a preset transportation time threshold value, and L2 is more than or equal to 1 and less than or equal to 5;
comparing and analyzing the supply quantity and the demand quantity;when in use
If so, judging that the supply quantity meets the requirement, and sending a logistics appointment signal to a logistics scheduling module through a processor; when in use
If so, judging that the supply quantity can not meet the requirement, and sending an inventory abnormal signal to a distributor through the processor; wherein
Is a predetermined scale factor, and
a real number greater than or equal to 0;
and sending the current order information and the order abnormal signals to a data storage module for storage through a processor, wherein the order abnormal signals comprise time abnormal signals and stock abnormal signals.
Preferably, the future order prediction unit is configured to predict a demand of a future order, and includes:
acquiring an order record in a data storage module through a processor, wherein the order record comprises a distributor name, a demand volume, demand time and weather data; the weather data are a temperature value, a humidity value and an air pressure value of the day with the required time;
preprocessing distributor names, demand time and weather data, converting the preprocessed distributor names, demand time and weather data into input data of a neural network model, and preprocessing demand quantity, and converting the preprocessed demand quantity into output data of the neural network model; the neural network model comprises an error feedforward neural network and an RBF neural network;
training the neural network model through input data and output data, and marking the trained neural network model as an intelligent model;
generating predicted input data; the forecast input data comprises a distributor name, preset time and preset weather data, wherein the preset weather data is the weather data of the preset time;
inputting the prediction input data into an intelligent model to obtain a prediction demand;
generating a prediction table according to the prediction time and the prediction demand;
and respectively sending the prediction table to a data storage module and a management scheduling module through a processor.
Preferably, the logistics scheduling module reserves the transportation vehicle after receiving the logistics reservation signal, and includes:
acquiring the demand and the delivery address in the current order information;
the logistics scheduling module calculates vehicle demands according to the demand; the vehicle demand and the distribution address are sent to a server of a logistics company; the vehicle requirements include a type of transport vehicle and a number of corresponding types;
the logistics company sends a feedback signal after processing the vehicle demand and the delivery address; the feedback signal comprises a logistics confirmation success signal and a logistics confirmation failure signal;
when the logistics scheduling module receives a logistics confirmation failure signal, the logistics scheduling module replaces a logistics company and sends the demand and the delivery address to a server of the replaced logistics company;
after receiving the logistics confirmation success signal, the logistics scheduling module sends a logistics confirmation signal to the management scheduling module through the processor;
when the time difference mark SC meets SC less than or equal to L1+2, sending a logistics rechecking signal to a logistics company server and acquiring a logistics feedback signal; the logistics feedback signal comprises a logistics rechecking confirmation success signal and a logistics rechecking failure signal;
when the logistics scheduling module receives a logistics rechecking confirmation success signal, the logistics rechecking normal signal is sent to the management scheduling module through the processor; when the logistics scheduling module receives a logistics rechecking failure signal, the logistics rechecking abnormal signal is sent to the management scheduling module through the processor;
and sending the sending records of the logistics confirmation signal, the logistics rechecking normal signal and the logistics rechecking abnormal signal to a data storage module for storage through the processor.
Preferably, the credit analysis module is used for evaluating the credit of the distributor, and comprises:
the distribution label is i, i ═ 1, 2, … …, n;
taking the total number of orders of distributor i and marking the total number of orders as DZi;
acquiring the overdue times of the payment of the distributor i and marking the overdue times of the payment as HYCi;
when the total number of orders DZi satisfies DZi < L3, no credit assessment is made for distributor i; wherein L3 is a preset order total threshold, and L3 is an integer greater than 0;
when the total number of orders DZi meets DZi not less than L3, acquiring a credit evaluation coefficient XPxi of distributor i; the credit evaluation coefficient XPxi is obtained by the formula
Wherein alpha 1 and alpha 2 are preset proportionality coefficients, and alpha 1 and alpha 2 are real numbers larger than 0;
carrying out descending arrangement on the credit evaluation coefficients XPxi to obtain a distributor credit evaluation table;
the distributor with the distributor credit evaluation table ranked as top L4 is marked as gold distributor; the distributor brand ranked as rear L5 in the distributor credit evaluation table is marked as a common distributor; the rest of the distributor marks in the distributor credit evaluation table are marked as silver distributors; wherein L4 and L5 are preset scaling factors greater than 0, and L4> L5;
the distributor credit evaluation table and the distributor mark are sent to a data storage module through a processor to be stored; the distribution trademarks include gold-plate distributors, silver-plate distributors and common distributors.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention is provided with a data analysis module, which is used for analyzing the current order information and predicting future orders; the processor marks the received order information as current order information and sends the current order information to the current order analysis unit; the current order analysis unit receives current order informationThen, acquiring the demand quantity, the delivery address and the demand time in the current order; acquiring a business address of a distributor corresponding to the current order information through a data storage module; matching the distribution address with the business address, and analyzing the demand when the matching is successful; when the matching fails, an address confirmation signal is sent to the distributor; the distributor confirms the address after receiving the address confirmation signal, sends the address confirmation signal to the current order analysis unit after the address confirmation is successful, and the order analysis unit analyzes the demand after receiving the address confirmation signal; acquiring a time difference value between the required time and the current time in real time, and marking the time difference value as SC; when the time difference SC satisfies SC<L1, judging that the current order can not be delivered in the specified time, and sending a time exception signal to the distributor through the processor; when the time difference SC is equal to or larger than SC 1, acquiring the stock quantity, and marking the stock quantity as KL; winning the daily output of the production workshop, and marking the daily output and the demand as RL and XQ respectively; acquiring a supply quantity GL; comparing and analyzing the supply quantity and the demand quantity; when in use
If so, judging that the supply quantity meets the requirement, and sending a logistics appointment signal to a logistics scheduling module through a processor; when in use
If so, judging that the supply quantity can not meet the requirement, and sending an inventory abnormal signal to a distributor through the processor; the data analysis module analyzes the feasibility of the order form through the distribution address, the stock and the demand time, and predicts the demand quantity of the future order form according to the historical data, so that the order form can be ensured to be processed in time, and the production plan of a production workshop can be arranged;
2. the invention sets a logistics scheduling module, which reserves the transport vehicle after receiving a logistics reservation signal; acquiring the demand and the delivery address in the current order information; the logistics scheduling module calculates vehicle demands according to the demand; the vehicle demand and the distribution address are sent to a server of a logistics company; the vehicle requirements include a type of transport vehicle and a number of corresponding types; the logistics company sends a feedback signal after processing the vehicle demand and the delivery address; when the logistics scheduling module receives a logistics confirmation failure signal, the logistics scheduling module replaces a logistics company and sends the demand and the delivery address to a server of the replaced logistics company; after receiving the logistics confirmation success signal, the logistics scheduling module sends a logistics confirmation signal to the management scheduling module through the processor; when the time difference mark SC meets SC less than or equal to L1+2, sending a logistics rechecking signal to a logistics company server and acquiring a logistics feedback signal; when the logistics dispatching module receives a logistics rechecking confirmation success signal, the logistics rechecking normal signal is sent to the management dispatching module through the processor; when the logistics scheduling module receives a logistics rechecking failure signal, the logistics rechecking abnormal signal is sent to the management scheduling module through the processor; the logistics scheduling module sends reservation information to a server of a logistics company according to the demand and the delivery address to reserve the transport vehicle and recheck logistics, so that the delivery efficiency of the food packaging film is improved, and the labor cost is reduced;
3. the invention designs the distribution system of the food packaging film, screens the orders of the distributors and reserves the logistics vehicles, reduces the manual participation, can ensure the reliability of the distributors and the accuracy of logistics distribution, can also predict the future demand, can reasonably arrange the production time and reduce the cost.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic diagram of the principle of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1, a distribution system of a food packaging film includes a processor, a credit analysis module, a management scheduling module, a data storage module, a user registration module, a data analysis module, and a logistics scheduling module;
the user registration module is used for registering the distributor and analyzing the registration information of the distributor;
the data analysis module is used for screening current order information and predicting future order information; the data analysis module comprises a current order analysis unit and a future order prediction unit;
the logistics scheduling module places an order according to the order information to obtain a logistics demand and sends the logistics demand to a logistics company; the logistics scheduling module is in communication connection with a server of a logistics company;
the credit analysis module is used for analyzing the credit of the distributor to obtain an analysis result and screening the distributor according to the analysis result.
Further, the distributor registers through the user registration module, including:
the distributor sends verification information to the user registration module through the intelligent terminal; the intelligent terminal comprises an intelligent mobile phone, a tablet personal computer and a notebook computer, and is in communication connection with the user registration module; the verification information comprises a business license, a legal representative, a mobile phone number of a legal person, a business address, a business range and a business period;
the processor identifies the authenticity of the business license, and when the business license is identified as authentic, the business range is analyzed; when the business license is identified as false, sending a business license exception signal to the intelligent terminal of the distributor;
acquiring a preset business range stored in a data storage module through a processor; the preset business range is a business range allowing a distributor to engage in food packaging film wholesale business;
matching the business range with a preset range, and judging that the business range meets the requirement when the matching is successful; when the matching fails, sending a business range abnormal signal to an intelligent terminal of a distributor;
and marking the distributor with the business range meeting the requirement as a qualified distributor, and sending the verification information of the qualified distributor to the data storage module for storage through the processor.
Further, the data analysis module is used for analyzing the current order information and predicting future orders, and comprises:
the processor marks the received order information as current order information and sends the current order information to the current order analysis unit;
the current order analysis unit acquires the demand, the delivery address and the demand time in the current order after receiving the current order information;
acquiring a business address of a distributor corresponding to the current order information through a data storage module; matching the distribution address with the business address, and analyzing the demand when the matching is successful; when the matching fails, an address confirmation signal is sent to the distributor; the distributor confirms the address after receiving the address confirmation signal, sends the address confirmation signal to the current order analysis unit after the address confirmation is successful, and the order analysis unit analyzes the demand after receiving the address confirmation signal;
acquiring a time difference value between the required time and the current time in real time, and marking the time difference value as SC;
when the time difference SC meets SC < L1, judging that the current order can not finish delivery at the specified time, and sending a time exception signal to the distributor through the processor; when the time difference SC is equal to or larger than SC 1, acquiring the stock quantity, and marking the stock quantity as KL; wherein L1 is a preset time difference threshold, and L1 is a real number greater than 0;
winning the daily output of the production workshop, and marking the daily output and the demand as RL and XQ respectively;
acquiring a supply quantity GL by a formula GL ═ KL + RL × (SC-L2); wherein L2 is a preset transportation time threshold value, and L2 is more than or equal to 1 and less than or equal to 5;
comparing and analyzing the supply quantity and the demand quantity; when in use
If so, judging that the supply quantity meets the requirement, and sending a logistics appointment signal to a logistics scheduling module through the processor; when the temperature is higher than the set temperature
If so, judging that the supply quantity can not meet the requirement, and sending an inventory abnormal signal to the distributor through the processor; wherein
Is a predetermined scale factor, and
a real number of 0 or more;
and sending the current order information and the order abnormal signals to a data storage module for storage through a processor, wherein the order abnormal signals comprise time abnormal signals and stock abnormal signals.
Further, the future order prediction unit is used for predicting the demand of the future order, and comprises:
acquiring an order record in a data storage module through a processor, wherein the order record comprises a distributor name, a demand quantity, demand time and weather data; the weather data is a temperature value, a humidity value and an air pressure value of the day with the required time;
preprocessing distributor names, demand time and weather data, converting the preprocessed distributor names, demand time and weather data into input data of a neural network model, and preprocessing demand quantity, and converting the preprocessed demand quantity into output data of the neural network model; the neural network model comprises an error feedforward neural network and an RBF neural network;
training the neural network model through input data and output data, and marking the trained neural network model as an intelligent model;
generating predicted input data; the forecast input data comprises a distributor name, preset time and preset weather data, and the preset weather data is the weather data of the preset time;
inputting the prediction input data into an intelligent model to obtain a prediction demand;
generating a prediction table according to the prediction time and the prediction demand;
and respectively sending the prediction table to a data storage module and a management scheduling module through a processor.
Further, the logistics scheduling module reserves the transport vehicle after receiving the logistics reservation signal, and the logistics scheduling module comprises:
acquiring the demand and the delivery address in the current order information;
the logistics scheduling module calculates vehicle demands according to the demand; the vehicle demand and the distribution address are sent to a server of a logistics company; the vehicle requirements include the type of transport vehicle and the number of corresponding types;
the logistics company sends a feedback signal after processing the vehicle demand and the delivery address; the feedback signal comprises a logistics confirmation success signal and a logistics confirmation failure signal;
when the logistics scheduling module receives a logistics confirmation failure signal, the logistics scheduling module replaces a logistics company and sends the demand and the delivery address to a server of the replaced logistics company;
after receiving the logistics confirmation success signal, the logistics scheduling module sends a logistics confirmation signal to the management scheduling module through the processor;
when the time difference is marked as SC less than or equal to L1+2, sending a logistics rechecking signal to a logistics company server and acquiring a logistics feedback signal; the logistics feedback signal comprises a logistics rechecking confirmation success signal and a logistics rechecking failure signal;
when the logistics dispatching module receives a logistics rechecking confirmation success signal, the logistics rechecking normal signal is sent to the management dispatching module through the processor; when the logistics scheduling module receives a logistics rechecking failure signal, the logistics rechecking abnormal signal is sent to the management scheduling module through the processor;
and sending the sending records of the logistics confirmation signal, the logistics rechecking normal signal and the logistics rechecking abnormal signal to a data storage module for storage through the processor.
Further, the credit analysis module is used for evaluating the credit of the distributor, and comprises:
the distribution label is i, i ═ 1, 2, … …, n;
acquiring the total number of orders of the distributor i and marking the total number of the orders as DZi;
acquiring the overdue times of the payment of the distributor i and marking the overdue times of the payment as HYCi;
when the total number of orders DZi satisfies DZi < L3, no credit assessment is made for distributor i; wherein L3 is a preset order total threshold, and L3 is an integer greater than 0;
when the total number of orders DZi meets DZi not less than L3, acquiring a credit evaluation coefficient XPxi of distributor i; the credit evaluation coefficient XPxi is obtained by the formula
Wherein alpha 1 and alpha 2 are preset proportionality coefficients, and alpha 1 and alpha 2 are real numbers larger than 0;
carrying out descending arrangement on the credit evaluation coefficients XPxi to obtain a distributor credit evaluation table;
the distributor trademark with the distributor credit evaluation table ranked as top L4 is marked as gold distributor; the distributor brand ranked as rear L5 in the distributor credit evaluation table is marked as a common distributor; the rest of the distributor marks in the distributor credit evaluation table are marked as silver distributors; wherein L4 and L5 are preset scaling factors greater than 0, and L4> L5;
the distributor credit evaluation table and the distributor mark are sent to a data storage module through a processor to be stored; the distribution trademarks include gold distributors, silver distributors, and common distributors.
Further, the processor is respectively in communication connection with the credit analysis module, the management scheduling module, the data storage module, the user registration module, the data analysis module and the logistics scheduling module; the data storage module is in communication connection with the management scheduling module.
The above formulas are all calculated by removing dimensions and taking values thereof, the formula is one closest to the real situation obtained by collecting a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The working principle of the invention is as follows:
the processor marks the received order information as current order information and sends the current order information to the current order analysis unit; the current order analysis unit receives the current order information and then acquires the demand quantity, the delivery address and the demand time in the current order; acquiring a business address of a distributor corresponding to the current order information through a data storage module; matching the distribution address with the business address, and analyzing the demand when the matching is successful; when the matching fails, an address confirmation signal is sent to the distributor; the distributor confirms the address after receiving the address confirmation signal, sends the address confirmation signal to the current order analysis unit after the address confirmation is successful, and the order analysis unit analyzes the demand after receiving the address confirmation signal; acquiring a time difference value between the required time and the current time in real time, and marking the time difference value as SC; when the time difference SC satisfies SC<L1, judging that the current order can not be delivered in the specified time, and sending a time exception signal to the distributor through the processor; when the time difference SC is equal to or larger than SC 1, acquiring the stock quantity, and marking the stock quantity as KL; winning the daily output of the production workshop, and marking the daily output and the demand as RL and XQ respectively; acquiring a supply quantity GL; comparing and analyzing the supply quantity and the demand quantity; when the temperature is higher than the set temperature
If so, judging that the supply quantity meets the requirement, and sending a logistics appointment signal to a logistics scheduling module through a processor; when in use
If so, judging that the supply quantity can not meet the requirement, and sending an inventory abnormal signal to a distributor through the processor;
acquiring the demand and the delivery address in the current order information; the logistics scheduling module calculates vehicle demands according to the demand; the vehicle demand and the distribution address are sent to a server of a logistics company; the vehicle requirements include a type of transport vehicle and a number of corresponding types; the logistics company sends a feedback signal after processing the vehicle demand and the delivery address; when the logistics scheduling module receives a logistics confirmation failure signal, the logistics scheduling module replaces a logistics company and sends the demand and the delivery address to a server of the replaced logistics company; after receiving the logistics confirmation success signal, the logistics scheduling module sends a logistics confirmation signal to the management scheduling module through the processor; when the time difference mark SC meets SC less than or equal to L1+2, sending a logistics rechecking signal to a logistics company server and acquiring a logistics feedback signal; when the logistics dispatching module receives a logistics rechecking confirmation success signal, the logistics rechecking normal signal is sent to the management dispatching module through the processor; when the logistics dispatching module receives the logistics rechecking failure signal, the logistics rechecking abnormal signal is sent to the management dispatching module through the processor.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (4)
1. A distribution system of food packaging films is characterized by comprising a processor, a credit analysis module, a management scheduling module, a data storage module, a user registration module, a data analysis module and a logistics scheduling module;
the user registration module is used for registering the distributor and analyzing the registration information of the distributor;
the data analysis module is used for screening current order information and predicting future order information; the data analysis module comprises a current order analysis unit and a future order prediction unit;
the logistics scheduling module places an order according to the order information to obtain a logistics demand and sends the logistics demand to a logistics company; the logistics scheduling module is in communication connection with a server of a logistics company;
the credit analysis module is used for analyzing the credit of the distributor to obtain an analysis result and screening the distributor according to the analysis result;
the future order prediction unit is used for predicting the demand of future orders and comprises the following steps:
acquiring an order record in a data storage module through a processor, wherein the order record comprises a distributor name, a demand volume, demand time and weather data; the weather data are a temperature value, a humidity value and an air pressure value of the day with the required time;
preprocessing distributor names, demand time and weather data, converting the preprocessed data into input data of a neural network model, and preprocessing demand quantity, and converting the preprocessed demand quantity into output data of the neural network model; the neural network model comprises an error feedforward neural network and an RBF neural network;
training the neural network model through input data and output data, and marking the trained neural network model as an intelligent model;
generating predicted input data; the forecast input data comprises a distributor name, preset time and preset weather data, wherein the preset weather data is the weather data of the preset time;
inputting the prediction input data into an intelligent model to obtain a prediction demand;
generating a prediction table according to the prediction time and the prediction demand;
respectively sending the prediction table to a data storage module and a management scheduling module through a processor;
the logistics scheduling module receives the logistics reservation signal and then reserves the transport vehicle, and the method comprises the following steps:
acquiring the demand and the delivery address in the current order information;
the logistics scheduling module calculates vehicle demands according to the demand; the vehicle demand and the distribution address are sent to a server of a logistics company; the vehicle requirements include a type of transport vehicle and a number of corresponding types;
the logistics company sends a feedback signal after processing the vehicle demand and the distribution address; the feedback signal comprises a logistics confirmation success signal and a logistics confirmation failure signal;
when the logistics scheduling module receives a logistics confirmation failure signal, the logistics scheduling module replaces a logistics company and sends the demand and the delivery address to a server of the replaced logistics company;
after receiving the logistics confirmation success signal, the logistics scheduling module sends a logistics confirmation signal to the management scheduling module through the processor;
when the time difference mark SC meets SC less than or equal to L1+2, sending a logistics rechecking signal to a logistics company server and acquiring a logistics feedback signal; the logistics feedback signal comprises a logistics rechecking confirmation success signal and a logistics rechecking failure signal; the time difference is obtained through a current order analysis unit, and L1 is a preset time difference threshold;
when the logistics dispatching module receives a logistics rechecking confirmation success signal, the logistics rechecking normal signal is sent to the management dispatching module through the processor; when the logistics scheduling module receives a logistics rechecking failure signal, the logistics rechecking abnormal signal is sent to the management scheduling module through the processor;
and sending the sending records of the logistics confirmation signal, the logistics rechecking normal signal and the logistics rechecking abnormal signal to a data storage module for storage through a processor.
2. The distribution system of a food packaging film according to claim 1, wherein a distributor registers through the user registration module, comprising:
the distributor sends verification information to the user registration module through the intelligent terminal; the intelligent terminal comprises an intelligent mobile phone, a tablet personal computer and a notebook computer, and is in communication connection with the user registration module; the verification information comprises a business license, a legal representative, a mobile phone number of a legal person, a business address, a business range and a business period;
the processor identifies the authenticity of the business license, and when the business license is identified as authentic, the business range is analyzed; when the business license is identified as false, sending a business license abnormal signal to the intelligent terminal of the distributor;
acquiring a preset business range stored in a data storage module through a processor; the preset business range is a business range allowing a distributor to engage in food packaging film wholesale business;
matching the business range with a preset range, and judging that the business range meets the requirement when the matching is successful; when the matching fails, sending a business range abnormal signal to an intelligent terminal of a distributor;
and marking the distributor with the business range meeting the requirement as a qualified distributor, and sending the verification information of the qualified distributor to the data storage module for storage through the processor.
3. The food packaging film distribution system of claim 1, wherein the data analysis module is configured to analyze current order information and predict future orders, comprising:
the processor marks the received order information as current order information and sends the current order information to the current order analysis unit;
the current order analysis unit receives the current order information and then acquires the demand quantity, the delivery address and the demand time in the current order;
acquiring a business address of a distributor corresponding to the current order information through a data storage module; matching the distribution address with the business address, and analyzing the demand when the matching is successful; when the matching fails, an address confirmation signal is sent to the distributor; the distributor confirms the address after receiving the address confirmation signal, sends the address confirmation signal to the current order analysis unit after the address confirmation is successful, and the order analysis unit analyzes the demand after receiving the address confirmation signal;
acquiring a time difference value between the required time and the current time in real time, and marking the time difference value as SC;
when the time difference SC meets SC < L1, judging that the current order can not finish delivery at the specified time, and sending a time exception signal to the distributor through the processor; when the time difference SC is equal to or larger than SC 1, acquiring the stock quantity, and marking the stock quantity as KL; wherein L1 is a preset time difference threshold, and L1 is a real number greater than 0;
acquiring the daily output of a production workshop, and respectively marking the daily output and the demand as RL and XQ;
acquiring a supply quantity GL by a formula GL ═ KL + RL × (SC-L2); wherein L2 is a preset transportation time threshold value, and L2 is more than or equal to 1 and less than or equal to 5;
comparing and analyzing the supply quantity and the demand quantity; when in use
If so, judging that the supply quantity meets the requirement, and sending a logistics appointment signal to a logistics scheduling module through a processor; when in use
If so, judging that the supply quantity can not meet the requirement, and sending an inventory abnormal signal to a distributor through the processor; wherein
Is a predetermined scale factor, and
a real number of 0 or more;
and sending the current order information and the order abnormal signals to a data storage module for storage through a processor, wherein the order abnormal signals comprise time abnormal signals and stock abnormal signals.
4. The food packaging film distribution system of claim 1, wherein the credit analysis module is configured to evaluate a credit of a distributor, and comprises:
the distribution label is i, i ═ 1, 2, … …, n;
taking the total number of orders of distributor i and marking the total number of orders as DZi;
acquiring the overdue times of the payment of the distributor i and marking the overdue times of the payment as HYCi;
when the total number of orders DZi satisfies DZi < L3, no credit assessment is made for distributor i; wherein L3 is a preset order total threshold, and L3 is an integer greater than 0;
when the total number of orders DZi meets DZi not less than L3, acquiring a credit evaluation coefficient XPxi of distributor i; the credit evaluation coefficient XPxi is obtained by the formula
Wherein alpha 1 and alpha 2 are preset proportionality coefficients, and alpha 1 and alpha 2 are real numbers larger than 0;
carrying out descending arrangement on the credit evaluation coefficients XPxi to obtain a distributor credit evaluation table;
the distributor trademark with the distributor credit evaluation table ranked as top L4 is marked as gold distributor; the distributor brand ranked as rear L5 in the distributor credit evaluation table is marked as a common distributor; the rest distributor marks in the distributor credit evaluation table are marked as silver distributors; wherein L4 and L5 are preset scaling factors greater than 0, and L4> L5;
sending the distributor credit evaluation table and the distributor mark to a data storage module for storage through a processor; the distribution trademarks include gold-plate distributors, silver-plate distributors and common distributors.
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