CN111553519A - Grain processing optimization method and device based on supply chain tracing evaluation system - Google Patents

Abstract

The invention discloses a grain processing optimization method and device based on a supply chain tracing evaluation system, wherein the method comprises the following steps: determining a tracing database according to supply chain information and supply chain data, determining production benefit influence factors of a target grain product according to grain processing benefit data, establishing a grain processing simulation model according to the production benefit influence factors, performing data analysis on the target tracing data in the tracing database according to the processing simulation model to obtain an analysis result, establishing a grain processing optimization model according to the analysis result, and optimizing the processing of the target grain product according to the grain processing optimization model; according to the invention, a high-quality target tracing database is established based on grain supply chain information, controllable factors in a processing link are determined, a simulation model and an optimization model of the processing link are established, working parameters of processing equipment are adjusted, and control on grain production and processing is realized.

Description

Grain processing optimization method and device based on supply chain tracing evaluation system

Technical Field

The invention relates to the technical field of grain processing, in particular to a grain processing optimization method and device based on a supply chain retrospective evaluation system.

Background

At present, most grain processing enterprises optimize a link of processing in a supply chain of the grain processing enterprises mostly from the aspects of improving processes, updating equipment and strengthening management, and do not analyze from the aspect of data and realize the optimization control of controllable factors in the processing process, so that the limited promotion of the processing link can be obtained, and the processes, the equipment updating and the strengthening management of the grain processing enterprises are not comprehensive, objective and incredible from a certain supply chain link or direction on the basis of no large amount of data analysis. Therefore, how to realize the optimization control of the controllable factors in the processing process of the grain processing enterprises, so as to optimize the production benefits of the grain processing enterprises is a technical problem to be solved urgently.

The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.

Disclosure of Invention

The invention mainly aims to provide a grain processing optimization method and device based on a supply chain retrospective evaluation system, and aims to solve the technical problem of optimizing and controlling controllable factors in the processing process of grain processing enterprises in the prior art so as to optimize the production benefits of the grain processing enterprises.

In order to achieve the purpose, the invention provides a grain processing optimization method based on a supply chain retroactive evaluation system, which comprises the following steps:

acquiring supply chain information, supply chain data and grain processing benefit data of a target grain product, and determining a tracing database according to the supply chain information and the supply chain data;

determining production benefit influence factors of the target grain product according to the grain processing benefit data, and establishing a grain processing simulation model according to the production benefit influence factors;

performing data analysis on the target tracing data in the tracing database according to the grain processing simulation model to obtain an analysis result;

determining a control variable and an optimization index according to the analysis result, and establishing a grain processing optimization model according to the control variable and the optimization index;

and determining a grain processing optimization strategy according to the grain processing optimization model, and optimizing the processing of the target grain product according to the grain processing optimization strategy.

Preferably, the obtaining supply chain information, supply chain data and grain processing benefit data of the target grain product, and determining a traceability database according to the supply chain information and the supply chain data includes:

acquiring supply chain information, supply chain data and grain processing benefit data of a target grain product, and determining a supply chain tracing evaluation system of the target grain product according to the supply chain information;

performing data extraction on the supply chain data of the target grain product according to the supply chain traceability evaluation system to obtain initial traceability data;

performing data fusion on the initial tracing data to obtain complete data;

and performing data screening on the complete data according to a preset screening model to obtain target tracing data, and generating a tracing database according to the target tracing data.

Preferably, the obtaining supply chain information, supply chain data and grain processing benefit data of the target grain product, and determining a supply chain traceability evaluation system of the target grain product according to the supply chain information includes:

acquiring supply chain information, supply chain data and grain processing benefit data of a target grain product, and determining a supply chain link of the target grain product according to the supply chain information;

determining an element layer of the supply chain link according to a preset element analysis model, and determining a tracing index of the element layer according to a preset index analysis model;

and establishing a supply chain retrospective evaluation system according to the supply chain links, the element layer and the retrospective indexes.

Preferably, the determining the production benefit influencing factor of the target grain product according to the grain processing benefit data and establishing a grain processing simulation model according to the production benefit influencing factor includes:

determining the benefit evaluation level of the target grain product according to the grain processing benefit data, and determining the production benefit influence factor of the benefit evaluation level according to a preset production benefit influence model;

and establishing a machining simulation model according to the production benefit influence factors.

Preferably, before performing data analysis on the target tracing data in the tracing database according to the grain processing simulation model and obtaining an analysis result, the method further includes:

judging whether the target tracing data in the tracing database meet preset conditions or not through a preset level judgment model, and obtaining a judgment result;

when the target tracing data do not meet the preset conditions, a preset multi-factor analysis of variance strategy is used as a target analysis strategy;

correspondingly, the step of performing data analysis on the target tracing data in the tracing database according to the grain processing simulation model to obtain an analysis result specifically includes:

and performing data analysis on the target tracing data in the tracing database according to the target analysis strategy and the machining simulation model to obtain an analysis result.

Preferably, the performing data analysis on the target tracing data in the tracing database according to the target analysis strategy and the machining simulation model to obtain an analysis result includes:

determining a significance value of target tracing data in the tracing database according to the target analysis strategy and the machining simulation model;

and judging whether the significance value meets a preset threshold value condition or not, obtaining a judgment result, and taking the judgment result as an analysis result.

Preferably, after the determining whether the target tracing data in the tracing database meets the preset condition by the preset level determination model and obtaining the determination result, the method further includes:

when the target tracing data meet the preset conditions, taking a preset correlation analysis strategy as a target analysis strategy;

correspondingly, the step of performing data analysis on the target tracing data in the tracing database according to the grain processing simulation model to obtain an analysis result specifically includes:

and performing data analysis on the target tracing data in the tracing database according to the target analysis strategy and the machining simulation model to obtain an analysis result.

In addition, in order to achieve the above object, the present invention further provides a grain processing optimization apparatus based on a supply chain retroactive evaluation system, including: the system comprises an acquisition module, a processing simulation model establishing module, an analysis module, an optimization model establishing module and an optimization module;

the acquisition module is used for acquiring supply chain information, supply chain data and grain processing benefit data of a target grain product and determining a traceability database according to the supply chain information and the supply chain data;

the processing simulation model establishing module is used for determining production benefit influence factors of the target grain product according to the grain processing benefit data and establishing a grain processing simulation model according to the production benefit influence factors;

the analysis module is used for carrying out data analysis on the target tracing data in the tracing database according to the grain processing simulation model to obtain an analysis result;

the optimization model establishing module is used for determining a control variable and an optimization index according to the analysis result and establishing a grain processing optimization model according to the control variable and the optimization index;

and the optimization module is used for determining a grain processing optimization strategy according to the grain processing optimization model and optimizing the processing of the target grain product according to the grain processing optimization strategy.

Preferably, the obtaining module is further configured to obtain supply chain information, supply chain data, and grain processing benefit data of a target grain product, and determine a supply chain traceability evaluation system of the target grain product according to the supply chain information;

the acquisition module is further used for performing data extraction on the supply chain data of the target grain product according to the supply chain traceability evaluation system to obtain initial traceability data;

the acquisition module is further used for carrying out data fusion on the initial tracing data to obtain complete data;

the acquisition module is further used for carrying out data screening on the complete data according to a preset screening model, obtaining target tracing data and generating a tracing database according to the target tracing data.

Preferably, the obtaining module is further configured to obtain supply chain information, supply chain data, and grain processing benefit data of a target grain product, and determine a supply chain link of the target grain product according to the supply chain information;

the acquisition module is further used for determining an element layer of the supply chain link according to a preset element analysis model and determining a tracing index of the element layer according to a preset index analysis model;

the acquisition module is further used for establishing a supply chain traceability evaluation system according to the supply chain links, the element layer and the traceability indexes.

In the invention, supply chain information, supply chain data and grain processing benefit data of a target grain product are acquired, a tracing database is determined according to the supply chain information and the supply chain data, determining the production benefit influence factor of the target grain product according to the grain processing benefit data, establishing a grain processing simulation model according to the production benefit influence factor, analyzing the data of the target tracing data in the tracing database according to the grain processing simulation model to obtain an analysis result, determining a control variable and an optimization index according to the analysis result, establishing a grain processing optimization model according to the control variable and the optimization index, determining a grain processing optimization strategy according to the grain processing optimization model, and optimizing the processing of the target grain product according to the grain processing optimization strategy; the method establishes a high-quality target tracing database based on the grain supply chain information, determines controllable factors in a processing link of a grain processing enterprise, establishes a simulation model and an optimization model of the processing link, adjusts working parameters of processing equipment, and realizes control of production benefits of the grain processing enterprise, thereby solving the technical problem of how to realize optimization control of the controllable factors in the processing process of the grain processing enterprise so as to optimize the production benefits of the grain processing enterprise.

Drawings

Fig. 1 is a schematic flow chart of a first embodiment of a grain processing optimization method based on a supply chain retroactive evaluation system according to the present invention;

FIG. 2 is a detailed representation of a trace back database according to an embodiment of the present invention;

FIG. 3 is a table-form illustration of the operating parameters of a processing tool in accordance with an embodiment of the present invention;

FIG. 4 is a schematic flow chart of a second embodiment of a grain processing optimization method based on a supply chain traceability evaluation system according to the present invention;

FIG. 5 is a schematic flow chart of a third embodiment of a grain processing optimization method based on a supply chain traceability evaluation system according to the present invention;

fig. 6 is a block diagram of a first embodiment of a grain processing optimization apparatus based on a supply chain traceability evaluation system according to the present invention.

The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.

Detailed Description

It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

Referring to fig. 1, fig. 1 is a schematic flow diagram of a first embodiment of a grain processing optimization method based on a supply chain retroactive evaluation system, and proposes the first embodiment of the grain processing optimization method based on the supply chain retroactive evaluation system.

In a first embodiment, the grain processing optimization method based on the supply chain retrospective evaluation system includes the following steps:

step S10: the method comprises the steps of obtaining supply chain information, supply chain data and grain processing benefit data of a target grain product, and determining a traceability database according to the supply chain information and the supply chain data.

It should be understood that the main implementation body of the present embodiment is the grain processing optimization device based on the supply chain retrospective evaluation system, wherein the grain processing optimization device based on the supply chain retrospective evaluation system may be an electronic device such as a personal computer or a server.

It should be noted that the supply chain information may be supply chain information stored by a grain processing enterprise when producing grain processing products; the supply chain data may be supply chain data stored by a grain processing enterprise when producing grain processing products; the grain processing benefit data can be data such as production and processing profit data, production and processing cost data, production and processing loss data, production and processing efficiency data and the like; the supply chain links can be all links from planting to dining table of the grain, for example, the supply chain links can be a planting link, a harvesting link, a storage link, a processing link, a transportation link, a market link, a dining table link and the like.

Understandably, the grain processing optimizing equipment based on the supply chain retrospective evaluation system acquires the supply chain information, the supply chain data and the grain processing benefit data of a target grain product, and determining that the retroactive database can be used for acquiring the supply chain information, the supply chain data and the grain processing benefit data of the target grain product according to the supply chain information and the supply chain data, and determining a supply chain traceability evaluation system of the target grain product according to the supply chain information, performing data extraction on the supply chain data of the target grain product according to the supply chain traceability evaluation system to obtain initial traceability data, and performing data fusion on the initial tracing data to obtain complete data, performing data screening on the complete data according to a preset screening model to obtain target tracing data, and generating a tracing database according to the target tracing data.

It should be understood that the grain processing optimization device based on the supply chain retroactive evaluation system determines the production benefit influencing factor of the target grain product according to the grain processing benefit data, and establishes the grain processing simulation model according to the production benefit influencing factor, which may be to acquire supply chain information, supply chain data and grain processing benefit data of the target grain product, determine the supply chain link of the target grain product according to the supply chain information, determine the element layer of the supply chain link according to a preset element analysis model, determine the retroactive index of the element layer according to a preset index analysis model, and establish the supply chain retroactive evaluation system according to the supply chain link, the element layer and the retroactive index, where a specific form of the supply chain retroactive evaluation system is shown in fig. 2.

Step S20: and determining the production benefit influence factors of the target grain product according to the grain processing benefit data, and establishing a grain processing simulation model according to the production benefit influence factors.

It can be understood that the grain processing optimization device based on the supply chain traceability evaluation system performs data analysis on the target traceability data in the traceability database according to the grain processing simulation model, and the obtained analysis result can be that the benefit evaluation level of the target grain product is determined according to the grain processing benefit data, the production benefit influence factor of the benefit evaluation level is determined according to a preset production benefit influence model, and the processing simulation model is established according to the production benefit influence factor.

It should be noted that the benefit evaluation level may be each processing stage in the processing process of the target grain product, for example, a raw grain and coarse grain selection stage, a grain grinding and grinding powdering stage, a finished grain sorting stage, and a byproduct utilization stage; the preset production benefit influence model can be production benefit influence information stored in a grain processing enterprise when producing grain processing products, for example, according to the characteristic difference of different grains and impurities contained in the grains in the aspects of size, density, shape, air resistance and friction impact, different processes and equipment (such as the wind speed of a fan and the size of a screen) are required to be adopted to remove the impurities; and adjusting the moisture according to the conditions required by the optimal processing effect; the variety of the grain and the working parameters of the grain grinding machine are as follows: the pressure between the rollers, the linear speed ratio and the like can influence the process effect, and the grain grinding strength (grain grinding pressure) can directly influence the breakage rate and the power consumption of grains; removing broken grains and impurities from the granular finished grain according to the grade standard, increasing the smoothness and improving the quality of the grain; the rice bran and corn germ produced in the processing process are used for preparing oil and extracting medical medicines.

Step S30: and performing data analysis on the target tracing data in the tracing database according to the grain processing simulation model to obtain an analysis result.

It should be understood that, the data analysis of the target tracing data in the tracing database according to the grain processing simulation model may obtain an analysis result by judging whether the target tracing data in the tracing database meets a preset condition through a preset level judgment model and obtaining a judgment result, when the target tracing data does not meet the preset condition, a preset multi-factor variance analysis strategy is used as a target analysis strategy, a significance value of the target tracing data in the tracing database is determined according to the target analysis strategy and the processing simulation model, whether the significance value meets a preset threshold condition is judged, a judgment result is obtained, and the judgment result is used as an analysis result;

or when the target tracing data meet the preset condition, taking a preset correlation analysis strategy as a target analysis strategy, and performing data analysis on the target tracing data in the tracing database according to the target analysis strategy and the machining simulation model to obtain an analysis result.

Step S40: and determining a control variable and an optimization index according to the analysis result, and establishing a grain processing optimization model according to the control variable and the optimization index.

It should be understood that the grain processing optimization equipment based on the supply chain traceability evaluation system determines the control variable and the optimization index according to the analysis result, and when the analysis result is that the homogeneity value of the variance is greater than the preset threshold value, the traceability index corresponding to the target traceability data is used as the optimization index, and the production benefit influence factor of the processing simulation model is used as the control variable.

It should be noted that, the total profit a, the grain yield b, the grain preparation rate c and the unit production cost d are set. The model with the maximum total profit of the objective function is:

a_max＝max(maxa_b,maxa_c,mina_d)

the grain processing optimization model is shown as the following formula:

P1：maxP

P2:min W_ii＝1,2,3,4,5,6

where P is the total profit, W_iEnergy consumption for each stage of the processing process (for example, energy consumption for grain cleaning sieve). x is the number of_1iI is 1, and 2 is the working parameters (the wind speed of a fan and the size of a screen) in the selection stage of the raw grain and the coarse grain; x is the number of_2iThe i is 1,2, 3 and 4, and the i is grain variety and the working parameters (pressure between rollers, linear speed and linear speed ratio) of the grain mill in the grain milling and flour milling stages; x is the number of_3iThe strength of the ground grain is obtained; x is the number of_4iAnd the parameters are related to the finishing stage of the finished product grain. Wherein c is_ijIndex parameters for each stageThe value is obtained. Through the optimization model, in order to meet the above targets, the working parameters of each link can be dynamically adjusted.

Step S50: and determining a grain processing optimization strategy according to the grain processing optimization model, and optimizing the processing of the target grain product according to the grain processing optimization strategy.

It should be noted that the optimization target of grain production and processing mainly includes the following three aspects: the optimal control problem is mainly embodied in that the working parameters of the processing equipment are adjusted to enable the economic index of grain production and processing to be optimal; the highest rice yield of the target grain product is obtained under the condition of ensuring the maximum profit and the minimum energy consumption of the grain processing enterprises; the market satisfaction of the target grain product is excellent.

Specifically, referring to fig. 3, fig. 3 is a table-form diagram of the operating parameters of the processing equipment in the embodiment of the present invention; if the working parameter of the grain cleaning sieve is a_1iObtaining the clean rice as a and the impurity as b_jThe power consumption is w_iReferring to fig. 3, the working parameters of other processing equipment are adjusted to minimize the power consumption, and the influence of the working parameters (control variables) of the processing equipment on the power consumption is analyzed. If the power consumption of a certain processing device is abnormal, the working parameters of the grain cleaning sieve are adjusted in time through the grain production and processing optimization strategy.

In the first embodiment, supply chain information, supply chain data and grain processing benefit data of a target grain product are acquired, a traceability database is determined according to the supply chain information and the supply chain data, determining the production benefit influence factor of the target grain product according to the grain processing benefit data, establishing a grain processing simulation model according to the production benefit influence factor, analyzing the data of the target tracing data in the tracing database according to the grain processing simulation model to obtain an analysis result, determining a control variable and an optimization index according to the analysis result, establishing a grain processing optimization model according to the control variable and the optimization index, determining a grain processing optimization strategy according to the grain processing optimization model, and optimizing the processing of the target grain product according to the grain processing optimization strategy; the method establishes a high-quality target tracing database based on the grain supply chain information, determines controllable factors in a processing link of a grain processing enterprise, establishes a simulation model and an optimization model of the processing link, adjusts working parameters of processing equipment, and realizes control of production benefits of the grain processing enterprise, thereby solving the technical problem of how to realize optimization control of the controllable factors in the processing process of the grain processing enterprise so as to optimize the production benefits of the grain processing enterprise.

Referring to fig. 4, fig. 4 is a schematic flow chart of a second embodiment of the grain processing optimization method based on a supply chain retroactive evaluation system, and the second embodiment of the grain processing optimization method based on the supply chain retroactive evaluation system is provided based on the first embodiment shown in fig. 1.

In the second embodiment, the step S10 includes:

step S101: the method comprises the steps of obtaining supply chain information, supply chain data and grain processing benefit data of a target grain product, and determining a supply chain tracing evaluation system of the target grain product according to the supply chain information.

It should be understood that the grain processing optimization device based on the supply chain retroactive evaluation system acquires supply chain information, supply chain data and grain processing benefit data of a target grain product, and determines the supply chain retroactive evaluation system of the target grain product according to the supply chain information, and determines a supply chain link of the target grain product according to the supply chain information, determines an element layer of the supply chain link according to a preset element analysis model, determines a retroactive index of the element layer according to a preset index analysis model, and establishes the supply chain retroactive evaluation system according to the supply chain link, the element layer and the retroactive index.

Further, the step S101 includes:

acquiring supply chain information, supply chain data and grain processing benefit data of a target grain product, and determining a supply chain link of the target grain product according to the supply chain information;

determining an element layer of the supply chain link according to a preset element analysis model, and determining a tracing index of the element layer according to a preset index analysis model;

and establishing a supply chain retrospective evaluation system according to the supply chain links, the element layer and the retrospective indexes.

It should be noted that the supply chain information may be supply chain information stored by a grain processing enterprise when producing grain processing products; the supply chain data may be supply chain data stored by a grain processing enterprise when producing grain processing products; the grain processing benefit data can be data such as production and processing profit data, production and processing cost data, production and processing loss data, production and processing efficiency data and the like; the supply chain links can be all links from planting to dining table of the grain, for example, the supply chain links can be a planting link, a harvesting link, a storage link, a processing link, a transportation link, a market link, a dining table link and the like.

It should be understood that the grain processing optimization device based on the supply chain retrospective evaluation system may determine the supply chain link of the target grain product according to the supply chain information by analyzing the supply chain information to determine the supply chain link of the target grain product.

It should be noted that the preset element analysis model may be a production benefit influence factor corresponding to each supply chain link set by the grain processing optimization equipment manufacturer based on the supply chain traceability evaluation system according to the test result; the preset index analysis model can be a traceability index corresponding to a production benefit influence factor set by a grain processing optimization equipment manufacturer based on a supply chain traceability evaluation system according to a test result.

It can be understood that the grain processing optimization equipment based on the supply chain tracing evaluation system determines an element layer of the supply chain link according to a preset element analysis model, and determines the tracing index of the element layer according to a preset index analysis model, wherein the tracing index can be a factor which can influence the production benefit of a grain processing enterprise in the supply chain link according to the preset element analysis model, for example, the planting link can be soil, variety, moisture, chemical fertilizer, pesticide, environment, mechanization level (or artificial planting), terrain (land quality, whether plain), population, market, production place dietary habits and the like, the harvesting link can be a harvesting mode (mechanical harvesting and artificial harvesting), a machine type, a drying mode, drying temperature, harvesting time, variety, weather, mechanical operators and the like, and the storage link can be storage time (long-time mildewing), The method comprises the steps of storage equipment, storage conditions (temperature and humidity), grain stack temperature, grain storage microbial influence, breakage rate (increasing the possibility of mildewing in storage) and the like, wherein the processing links can be raw grain selection, grain grinding, finished grain finishing, byproduct utilization, processing technology, processing time, processing amount, raw grain quality, raw grain treatment (operation of cleaning moisture) and the like, and the transportation links can be transportation tools, transportation conditions (temperature and weather), mildewing, packaging damage, leakage and the like.

It should be noted that, specifically, the first layer in the supply chain retrospective evaluation system is the supply chain link layer, and the mathematical expression of the supply chain link layer x is as follows:

{x₁,x₂,…,x_m}

wherein x is_mIs the mth supply chain link in the production of the processed product.

Determining the element layer of the supply chain link according to a preset element analysis model, wherein the expression forms of the element layers under different supply chains are as follows:

x_n

{y_n0,y_n1,…,y_nk}

wherein, y_n0Basic information layer of the nth supply chain link for rice consumption, y_n1～y_nkK layers of elements affecting the productivity of the grain processing plant in n supply chain segments, e.g. in the storage segment of the supply chain, y_n1～y_nkThe factors such as storage time, storage equipment, and storage conditions (temperature and humidity) are shown.

Designing the tracing indexes of a basic information layer and an element layer of a supply chain link, wherein the z expression forms of the tracing index layers of different elements under different supply chain links are as follows:

x_n

y_nl

{z_nl1,z_nl2,…,z_nlp}

wherein z is_nl1The method is a retroactive index collection of the factor I which influences the production benefits of grain processing enterprises in the nth supply chain link. For example, in the grain processing process, the grain breakage rate directly affects the production efficiency of grain processing enterprises, and if the grain breakage rate is increased, the supply chain traceability evaluation system can be used for finding out which elements in the grain processing link cause the increase of the grain breakage rate.

A supply chain traceability evaluation system of a processed product produced by a grain processing enterprise is established by combining a supply chain link layer, an element layer and a traceability index layer, and the expression form of the supply chain traceability evaluation system can be as follows:

supply chain link x { x₁,x₂,...,x_m}

Element layer y { y₁₀,y₁₁,...,y_1k1},{y₂₀,y₂₁,...,y_2k2},...{y_m0,y_m1,...,y_mkm}

Tracing index z { z₁₀₁,z₁₀₂,...,z_10p10},{z₁₁₁,z₁₁₂,...,z_11p11},...{z_mkm1,z_mkm2,...,z_mkmpkm}

Wherein x is_nIs the nth supply chain link, y, of the target grain product_n0A basic information layer at the nth supply chain link for the target grain product, wherein the basic information layer can be designed according to the target grain product, y_n1～y_nkK element layers, z, for which the nth supply chain link may have an impact on the production efficiency of the grain processing enterprise_nkmpkmIs the kth supply chain link which can influence the production benefit of the grain processing enterprise^mP-th in element layer^kmAnd (4) tracing indexes.

Step S102: and performing data extraction on the supply chain data of the target grain product according to the supply chain traceability evaluation system to obtain initial traceability data.

It should be understood that the grain processing optimization equipment based on the supply chain retroactive evaluation system performs data extraction on the supply chain data of the target grain product according to the supply chain retroactive evaluation system, and the obtaining of the retroactive data may be performing data extraction on the supply chain data of each batch of target grain product to obtain initial retroactive data meeting the supply chain retroactive evaluation system.

Step S103: and carrying out data fusion on the initial tracing data to obtain complete data.

It should be understood that the grain processing optimization equipment based on the supply chain traceability evaluation system performs data fusion on the initial traceability data to obtain complete data, and the complete data can be obtained by performing targeted association level fusion, feature level fusion, demand level fusion and the like on the initial traceability data of different supply chain links at different time points and space points.

Step S104: and performing data screening on the complete data according to a preset screening model to obtain target tracing data, and generating a tracing database according to the target tracing data.

It should be understood that the grain processing optimization equipment based on the supply chain traceability evaluation system performs data screening on the complete data according to a preset screening model, and the target traceability data can be obtained by performing index screening on a complete index corresponding to the complete data according to the preset screening model to obtain a main index, and performing data extraction on the complete data according to the main index to obtain target traceability data; and generating a tracing database according to the target tracing data, wherein the specific expression form of the tracing database is shown in fig. 2.

Understandably, the grain processing optimization equipment based on the supply chain retrospective evaluation system performs index screening on the complete indexes corresponding to the complete data according to the preset screening modelThe main index may be obtained by selecting a group of necessary and representative indexes from the indexes in each link, wherein p (p ═ n × k) indexes are total, and selecting one index x which is not related to other indexes most_ni(indicating that this indicator cannot be replaced by another indicator). Selecting one index from the remaining p-1 indexes_niLeast relevant index x_njWill (x)_ni，x_nj) Are combined. And selecting the index which is not related to the most from the remaining p-2 indexes, and continuing until the remaining p-m indexes are all closely related to the selected indexes, which indicates that the remaining m indexes can be replaced by the selected indexes. The expression form of the main indexes is as follows:

{α₁，α₂，...，α_m}{β₁，β₂，...，β_m}...{x₁，x₂，...，x_m}

in the second embodiment, the step S20 includes:

step S201: and determining the benefit evaluation level of the target grain product according to the grain processing benefit data, and determining the production benefit influence factor of the benefit evaluation level according to a preset production benefit influence model.

It should be noted that the benefit evaluation level may be each processing stage in the processing process of the target grain product, for example, a raw grain and coarse grain selection stage, a grain grinding and grinding powdering stage, a finished grain sorting stage, and a byproduct utilization stage; the preset production benefit influence model can be production benefit influence information stored in a grain processing enterprise when producing grain processing products, for example, according to the characteristic difference of different grains and impurities contained in the grains in the aspects of size, density, shape, air resistance and friction impact, different processes and equipment (such as the wind speed of a fan and the size of a screen) are required to be adopted to remove the impurities; and adjusting the moisture according to the conditions required by the optimal processing effect; the variety of the grain and the working parameters of the grain grinding machine are as follows: the pressure between the rollers, the linear speed ratio and the like can influence the process effect, and the grain grinding strength (grain grinding pressure) can directly influence the breakage rate and the power consumption of grains; removing broken grains and impurities from the granular finished grain according to the grade standard, increasing the smoothness and improving the quality of the grain; the rice bran and corn germ produced in the processing process are used for preparing oil and extracting medical medicines.

Step S202: and establishing a machining simulation model according to the production benefit influence factors.

It should be understood that the grain processing optimization equipment based on the supply chain retrospective evaluation system can establish a processing simulation model according to the production benefit influence factors.

In a second embodiment, supply chain information, supply chain data, and grain processing benefit data for a target grain product are obtained, and determining a supply chain traceability evaluation system of the target grain product according to the supply chain information, performing data extraction on the supply chain data of the target grain product according to the supply chain traceability evaluation system to obtain initial traceability data, performing data fusion on the initial tracing data to obtain complete data, performing data screening on the complete data according to a preset screening model to obtain target tracing data, generating a tracing database according to the target tracing data, determining the benefit evaluation level of the target grain product according to the grain processing benefit data, determining the production benefit influence factor of the benefit evaluation level according to a preset production benefit influence model, and establishing a processing simulation model according to the production benefit influence factor; according to the embodiment, a supply chain tracing evaluation system is determined through supply chain information, and a processing simulation model is determined through grain processing benefit data, so that production data of a target grain product in a production process can be comprehensively analyzed.

Referring to fig. 5, fig. 5 is a schematic flow chart of a grain processing optimization method based on a supply chain retroactive evaluation system according to a third embodiment of the present invention, and the third embodiment of the grain processing optimization method based on the supply chain retroactive evaluation system according to the present invention is provided based on the first embodiment shown in fig. 1.

In the third embodiment, before the step S30, the method further includes:

step S301: and judging whether the target tracing data in the tracing database meet preset conditions or not through a preset level judgment model, and obtaining a judgment result.

It should be noted that, the judging whether the target tracing data in the tracing database meets the preset condition through the preset level judging model may be judging whether the tracing data in the tracing database can be divided into different levels, for example, whether different fertilizing amounts and different varieties have influence on the crop yield in a planting link, and if so, the fertilizing amounts and the varieties can be divided into different levels.

Step S302: and when the target tracing data does not meet the preset condition, taking a preset multi-factor analysis of variance strategy as a target analysis strategy.

It should be noted that the preset multi-factor analysis of variance strategy may be a multi-factor analysis of variance method, and whether the multiple factors have significant influence on the dependent variable is determined by a process of hypothesis testing by using a variance comparison method.

Accordingly, the step S30 includes:

step S30': and performing data analysis on the target tracing data in the tracing database according to the target analysis strategy and the machining simulation model to obtain an analysis result.

After step S301, the method further includes:

step S302': and when the target tracing data meet the preset conditions, taking a preset correlation analysis strategy as a target analysis strategy.

It can be understood that, when the judgment results satisfy the same level, a preset correlation analysis strategy is taken as a target analysis strategy, where the preset correlation analysis strategy may be any method for correlation analysis, and this embodiment is not limited thereto.

In a third embodiment, whether target tracing data in the tracing database meet a preset condition is judged through a preset level judgment model, a judgment result is obtained, and when the target tracing data do not meet the preset condition, a preset multi-factor analysis of variance strategy is used as a target analysis strategy; when the target tracing data meet the preset conditions, a preset correlation analysis strategy is used as a target analysis strategy, and data analysis is carried out on the target tracing data in the tracing database according to the target analysis strategy and the machining simulation model to obtain an analysis result; in the embodiment, basic information influencing the production benefit of the grain processing enterprise and an influence rule of influencing factors in each supply chain link are determined through multi-factor variance analysis and correlation analysis, so that the production benefit of the grain processing enterprise can be optimized in an all-around manner.

In addition, referring to fig. 6, an embodiment of the present invention further provides a grain processing optimization apparatus based on a supply chain retroactive evaluation system, where the grain processing optimization apparatus based on the supply chain retroactive evaluation system includes: the system comprises an acquisition module 10, a machining simulation model establishing module 20, an analysis module 30, an optimization model establishing module 40 and an optimization module 50;

the obtaining module 10 is configured to obtain supply chain information, supply chain data, and grain processing benefit data of a target grain product, and determine a traceability database according to the supply chain information and the supply chain data.

It should be understood that the main implementation body of the present embodiment is the grain processing optimization device based on the supply chain retrospective evaluation system, wherein the grain processing optimization device based on the supply chain retrospective evaluation system may be an electronic device such as a personal computer or a server.

It should be noted that the supply chain information may be supply chain information stored by a grain processing enterprise when producing grain processing products; the supply chain data may be supply chain data stored by a grain processing enterprise when producing grain processing products; the grain processing benefit data can be data such as production and processing profit data, production and processing cost data, production and processing loss data, production and processing efficiency data and the like; the supply chain links can be all links from planting to dining table of the grain, for example, the supply chain links can be a planting link, a harvesting link, a storage link, a processing link, a transportation link, a market link, a dining table link and the like.

Understandably, the grain processing optimizing equipment based on the supply chain retrospective evaluation system acquires the supply chain information, the supply chain data and the grain processing benefit data of a target grain product, and determining that the retroactive database can be used for acquiring the supply chain information, the supply chain data and the grain processing benefit data of the target grain product according to the supply chain information and the supply chain data, and determining a supply chain traceability evaluation system of the target grain product according to the supply chain information, performing data extraction on the supply chain data of the target grain product according to the supply chain traceability evaluation system to obtain initial traceability data, and performing data fusion on the initial tracing data to obtain complete data, performing data screening on the complete data according to a preset screening model to obtain target tracing data, and generating a tracing database according to the target tracing data.

It should be understood that the grain processing optimization device based on the supply chain retroactive evaluation system determines the production benefit influencing factor of the target grain product according to the grain processing benefit data, and establishes the grain processing simulation model according to the production benefit influencing factor, which may be to acquire supply chain information, supply chain data and grain processing benefit data of the target grain product, determine the supply chain link of the target grain product according to the supply chain information, determine the element layer of the supply chain link according to a preset element analysis model, determine the retroactive index of the element layer according to a preset index analysis model, and establish the supply chain retroactive evaluation system according to the supply chain link, the element layer and the retroactive index, where a specific form of the supply chain retroactive evaluation system is shown in fig. 2.

The processing simulation model establishing module 20 is configured to determine a production benefit influencing factor of the target grain product according to the grain processing benefit data, and establish a grain processing simulation model according to the production benefit influencing factor.

It can be understood that the grain processing optimization device based on the supply chain traceability evaluation system performs data analysis on the target traceability data in the traceability database according to the grain processing simulation model, and the obtained analysis result can be that the benefit evaluation level of the target grain product is determined according to the grain processing benefit data, the production benefit influence factor of the benefit evaluation level is determined according to a preset production benefit influence model, and the processing simulation model is established according to the production benefit influence factor.

It should be noted that the benefit evaluation level may be each processing stage in the processing process of the target grain product, for example, a raw grain and coarse grain selection stage, a grain grinding and grinding powdering stage, a finished grain sorting stage, and a byproduct utilization stage; the preset production benefit influence model can be production benefit influence information stored in a grain processing enterprise when producing grain processing products, for example, according to the characteristic difference of different grains and impurities contained in the grains in the aspects of size, density, shape, air resistance and friction impact, different processes and equipment (such as the wind speed of a fan and the size of a screen) are required to be adopted to remove the impurities; and adjusting the moisture according to the conditions required by the optimal processing effect; the variety of the grain and the working parameters of the grain grinding machine are as follows: the pressure between the rollers, the linear speed ratio and the like can influence the process effect, and the grain grinding strength (grain grinding pressure) can directly influence the breakage rate and the power consumption of grains; removing broken grains and impurities from the granular finished grain according to the grade standard, increasing the smoothness and improving the quality of the grain; the rice bran and corn germ produced in the processing process are used for preparing oil and extracting medical medicines.

And the analysis module 30 is configured to perform data analysis on the target tracing data in the tracing database according to the grain processing simulation model to obtain an analysis result.

It should be understood that, the data analysis of the target tracing data in the tracing database according to the grain processing simulation model may obtain an analysis result by judging whether the target tracing data in the tracing database meets a preset condition through a preset level judgment model and obtaining a judgment result, when the target tracing data does not meet the preset condition, a preset multi-factor variance analysis strategy is used as a target analysis strategy, a significance value of the target tracing data in the tracing database is determined according to the target analysis strategy and the processing simulation model, whether the significance value meets a preset threshold condition is judged, a judgment result is obtained, and the judgment result is used as an analysis result;

or when the target tracing data meet the preset condition, taking a preset correlation analysis strategy as a target analysis strategy, and performing data analysis on the target tracing data in the tracing database according to the target analysis strategy and the machining simulation model to obtain an analysis result.

And the optimization model establishing module 40 is configured to determine a control variable and an optimization index according to the analysis result, and establish a grain processing optimization model according to the control variable and the optimization index.

It should be understood that the grain processing optimization equipment based on the supply chain traceability evaluation system determines the control variable and the optimization index according to the analysis result, and when the analysis result is that the homogeneity value of the variance is greater than the preset threshold value, the traceability index corresponding to the target traceability data is used as the optimization index, and the production benefit influence factor of the processing simulation model is used as the control variable.

It should be noted that, the total profit a, the grain yield b, the grain preparation rate c and the unit production cost d are set. The model with the maximum total profit of the objective function is:

a_max＝max(maxa_b,maxa_c,mina_d)

the grain processing optimization model is shown as the following formula:

P1：max P

P2:min W_ii＝1,2,3,4,5,6

where P is the total profit, W_iEnergy consumption for each stage of the processing process (for example, energy consumption for grain cleaning sieve). x is the number of_1iI is 1, and 2 is the working parameters (the wind speed of a fan and the size of a screen) in the selection stage of the raw grain and the coarse grain; x is the number of_2iI is 1,2, 3,4 is grain in the stage of grinding grain or grinding grain into powderThe variety of the food and the working parameters (pressure between rollers, linear speed and linear speed ratio) of the grain grinder; x is the number of_3iThe strength of the ground grain is obtained; x is the number of_4iAnd the parameters are related to the finishing stage of the finished product grain. Wherein c is_ijThe index parameter values of each stage are obtained. Through the optimization model, in order to meet the above targets, the working parameters of each link can be dynamically adjusted.

And the optimization module 50 is configured to determine a grain processing optimization strategy according to the grain processing optimization model, and optimize the processing of the target grain product according to the grain processing optimization strategy.

It should be noted that the optimization target of grain production and processing mainly includes the following three aspects: the optimal control problem is mainly embodied in that the working parameters of the processing equipment are adjusted to enable the economic index of grain production and processing to be optimal; the highest rice yield of the target grain product is obtained under the condition of ensuring the maximum profit and the minimum energy consumption of the grain processing enterprises; the market satisfaction of the target grain product is excellent.

Specifically, referring to fig. 3, fig. 3 is a table-form diagram of the operating parameters of the processing equipment in the embodiment of the present invention; if the working parameter of the grain cleaning sieve is a_1iObtaining the clean rice as a and the impurity as b_jThe power consumption is w_iReferring to fig. 3, the working parameters of other processing equipment are adjusted to minimize the power consumption, and the influence of the working parameters (control variables) of the processing equipment on the power consumption is analyzed. If the power consumption of a certain processing device is abnormal, the working parameters of the grain cleaning sieve are adjusted in time through the grain production and processing optimization strategy.

In the embodiment, the supply chain information, the supply chain data and the grain processing benefit data of the target grain product are acquired, and the tracing database is determined according to the supply chain information and the supply chain data, determining the production benefit influence factor of the target grain product according to the grain processing benefit data, establishing a grain processing simulation model according to the production benefit influence factor, analyzing the data of the target tracing data in the tracing database according to the grain processing simulation model to obtain an analysis result, determining a control variable and an optimization index according to the analysis result, establishing a grain processing optimization model according to the control variable and the optimization index, determining a grain processing optimization strategy according to the grain processing optimization model, and optimizing the processing of the target grain product according to the grain processing optimization strategy; the method and the device establish a high-quality target tracing database based on the grain supply chain information, determine controllable factors in a processing link of a grain processing enterprise, establish a simulation model and an optimization model of the processing link, adjust working parameters of processing equipment, and realize control over production benefits of the grain processing enterprise, so that the technical problem of how to realize optimization control over the controllable factors in the processing process of the grain processing enterprise and optimize the production benefits of the grain processing enterprise is solved.

In an embodiment, the obtaining module is further configured to obtain supply chain information, supply chain data, and grain processing benefit data of a target grain product, and determine a supply chain traceability evaluation system of the target grain product according to the supply chain information;

the acquisition module is further used for performing data extraction on the supply chain data of the target grain product according to the supply chain traceability evaluation system to obtain initial traceability data;

the acquisition module is further used for carrying out data fusion on the initial tracing data to obtain complete data;

the acquisition module is further used for carrying out data screening on the complete data according to a preset screening model, obtaining target tracing data and generating a tracing database according to the target tracing data.

In an embodiment, the obtaining module is further configured to obtain supply chain information, supply chain data, and grain processing benefit data of a target grain product, and determine a supply chain link of the target grain product according to the supply chain information;

the acquisition module is further used for determining an element layer of the supply chain link according to a preset element analysis model and determining a tracing index of the element layer according to a preset index analysis model;

the acquisition module is further used for establishing a supply chain traceability evaluation system according to the supply chain links, the element layer and the traceability indexes.

Other embodiments or specific implementation manners of the grain processing optimization device based on the supply chain traceability evaluation system can refer to the above method embodiments, and are not described herein again.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order, but rather the words first, second, third, etc. are to be interpreted as names.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be substantially implemented or a part contributing to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g., a Read Only Memory (ROM)/Random Access Memory (RAM), a magnetic disk, an optical disk), and includes several instructions for enabling a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.

The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (10)

1. A grain processing optimization method based on a supply chain retroactive evaluation system is characterized by comprising the following steps of:

acquiring supply chain information, supply chain data and grain processing benefit data of a target grain product, and determining a tracing database according to the supply chain information and the supply chain data;

determining production benefit influence factors of the target grain product according to the grain processing benefit data, and establishing a grain processing simulation model according to the production benefit influence factors;

performing data analysis on the target tracing data in the tracing database according to the grain processing simulation model to obtain an analysis result;

determining a control variable and an optimization index according to the analysis result, and establishing a grain processing optimization model according to the control variable and the optimization index;

and determining a grain processing optimization strategy according to the grain processing optimization model, and optimizing the processing of the target grain product according to the grain processing optimization strategy.

2. The grain processing optimization method based on the supply chain traceability evaluation system of claim 1, wherein the step of obtaining the supply chain information, the supply chain data and the grain processing benefit data of the target grain product and determining the traceability database according to the supply chain information and the supply chain data specifically comprises:

acquiring supply chain information, supply chain data and grain processing benefit data of a target grain product, and determining a supply chain tracing evaluation system of the target grain product according to the supply chain information;

performing data extraction on the supply chain data of the target grain product according to the supply chain traceability evaluation system to obtain initial traceability data;

performing data fusion on the initial tracing data to obtain complete data;

and performing data screening on the complete data according to a preset screening model to obtain target tracing data, and generating a tracing database according to the target tracing data.

3. The grain processing optimization method based on the supply chain traceability evaluation system of claim 1, wherein the step of obtaining the supply chain information, the supply chain data and the grain processing benefit data of the target grain product and determining the supply chain traceability evaluation system of the target grain product according to the supply chain information specifically comprises:

acquiring supply chain information, supply chain data and grain processing benefit data of a target grain product, and determining a supply chain link of the target grain product according to the supply chain information;

determining an element layer of the supply chain link according to a preset element analysis model, and determining a tracing index of the element layer according to a preset index analysis model;

and establishing a supply chain retrospective evaluation system according to the supply chain links, the element layer and the retrospective indexes.

4. The grain processing optimization method based on the supply chain traceability evaluation system of claim 1, wherein the step of determining the production benefit influencing factor of the target grain product according to the grain processing benefit data and establishing a grain processing simulation model according to the production benefit influencing factor specifically comprises:

determining the benefit evaluation level of the target grain product according to the grain processing benefit data, and determining the production benefit influence factor of the benefit evaluation level according to a preset production benefit influence model;

and establishing a machining simulation model according to the production benefit influence factors.

5. The grain processing optimization method based on the supply chain traceability evaluation system of claim 1, wherein before the step of analyzing the target traceability data in the traceability database according to the grain processing simulation model to obtain the analysis result, the grain processing optimization method based on the supply chain traceability evaluation system further comprises:

judging whether the target tracing data in the tracing database meet preset conditions or not through a preset level judgment model, and obtaining a judgment result;

when the target tracing data do not meet the preset conditions, a preset multi-factor analysis of variance strategy is used as a target analysis strategy;

correspondingly, the step of performing data analysis on the target tracing data in the tracing database according to the grain processing simulation model to obtain an analysis result specifically includes:

and performing data analysis on the target tracing data in the tracing database according to the target analysis strategy and the machining simulation model to obtain an analysis result.

6. The grain processing optimization method based on the supply chain traceability evaluation system of claim 5, wherein the step of performing data analysis on the target traceability data in the traceability database according to the target analysis strategy and the processing simulation model to obtain an analysis result specifically comprises:

determining a significance value of target tracing data in the tracing database according to the target analysis strategy and the machining simulation model;

and judging whether the significance value meets a preset threshold value condition or not, obtaining a judgment result, and taking the judgment result as an analysis result.

7. The grain processing optimization method based on the supply chain retrospective evaluation system according to claim 5, wherein after the step of determining whether the target retrospective data in the retrospective database satisfies the predetermined condition by the predetermined level determination model and obtaining the determination result, the grain processing optimization method based on the supply chain retrospective evaluation system further comprises:

when the target tracing data meet the preset conditions, taking a preset correlation analysis strategy as a target analysis strategy;

correspondingly, the step of performing data analysis on the target tracing data in the tracing database according to the grain processing simulation model to obtain an analysis result specifically includes:

and performing data analysis on the target tracing data in the tracing database according to the target analysis strategy and the machining simulation model to obtain an analysis result.

8. A grain processing optimization device based on a supply chain retrospective evaluation system is characterized by comprising the following components: the system comprises an acquisition module, a processing simulation model establishing module, an analysis module, an optimization model establishing module and an optimization module;

the acquisition module is used for acquiring supply chain information, supply chain data and grain processing benefit data of a target grain product and determining a traceability database according to the supply chain information and the supply chain data;

the processing simulation model establishing module is used for determining production benefit influence factors of the target grain product according to the grain processing benefit data and establishing a grain processing simulation model according to the production benefit influence factors;

the analysis module is used for carrying out data analysis on the target tracing data in the tracing database according to the grain processing simulation model to obtain an analysis result;

the optimization model establishing module is used for determining a control variable and an optimization index according to the analysis result and establishing a grain processing optimization model according to the control variable and the optimization index;

and the optimization module is used for determining a grain processing optimization strategy according to the grain processing optimization model and optimizing the processing of the target grain product according to the grain processing optimization strategy.

9. The grain processing optimization device based on the supply chain retroactive evaluation system of claim 8, wherein the obtaining module is further configured to obtain supply chain information, supply chain data and grain processing benefit data of a target grain product, and determine the supply chain retroactive evaluation system of the target grain product according to the supply chain information;

the acquisition module is further used for performing data extraction on the supply chain data of the target grain product according to the supply chain traceability evaluation system to obtain initial traceability data;

the acquisition module is further used for carrying out data fusion on the initial tracing data to obtain complete data;

the acquisition module is further used for carrying out data screening on the complete data according to a preset screening model, obtaining target tracing data and generating a tracing database according to the target tracing data.

10. The grain processing optimization device based on a supply chain traceability evaluation system of claim 9, wherein the obtaining module is further configured to obtain supply chain information, supply chain data and grain processing benefit data of a target grain product, and determine a supply chain link of the target grain product according to the supply chain information;

the acquisition module is further used for determining an element layer of the supply chain link according to a preset element analysis model and determining a tracing index of the element layer according to a preset index analysis model;

the acquisition module is further used for establishing a supply chain traceability evaluation system according to the supply chain links, the element layer and the traceability indexes.

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