CN115345487A - Cigarette classification method and system - Google Patents
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Abstract
The invention discloses a cigarette classification method, which comprises the steps of acquiring historical production data of a product gauge, analyzing the historical production data of the product gauge, aggregating the product gauges with similar module types and proportions into a formula platform, obtaining the demand of a module according to the demand of the product gauge in the next production cycle, reasonably and scientifically combining module purchase with the structural layout of an integral cigarette product, and further mining the applicability of the module. The invention also provides a cigarette classification system, which corresponds to the steps of the method one by one and has the same beneficial effect.
Description
Technical Field
The invention relates to the technical field of cigarette classification storage, in particular to a cigarette classification method and system.
Background
The raw tobacco is the tobacco leaves which are roasted by fresh tobacco leaves, and the raw tobacco is formed into a module after threshing and redrying. The module refers to a combination of kinds and numbers of various raw cigarettes. The cigarette formula refers to the number and proportion of modules used in each product specification, and the modules are the minimum units of the cigarette formula. The pin gauge refers to the specification of cigarettes, such as Huang He Lou 1916 and hong jin Long hard blue love you, which we call two different pin gauges.
The cigarette has numerous products and complex and changeable formula, the related production procedures are various, and great difficulty is brought to the purchase of tobacco leaves. At present, enterprises for researching tobacco purchasing layout strategies exist in the industry, but the enterprises only carry out simple analysis from annual data, and are not combined with the structural layout of the whole cigarette product, and the rationality and the scientificity need to be further examined. The classification of cigarettes is mostly based on the experience and smoking evaluation of formulators, and although the research on the applicability of tobacco leaves is also related, the use value of the tobacco leaves is improved, but the cigarette is not combined with product layout, and the balance rationality of tobacco leaf purchase and use is not really achieved. Therefore, a standard formula is necessary to be established, and the cigarettes are classified based on the similarity of the standard formula, so that the requirement of the module can be deduced from the requirement of the standard specification, and data support is provided for accurate purchase and reasonable use of tobacco raw materials.
Therefore, the technical personnel in the field need to solve the problem that the cigarette classification method and the cigarette classification system can ensure the balance rationality of tobacco leaf purchase and use and can acquire the demand of each module in the next production cycle according to historical data.
Disclosure of Invention
The invention aims to provide a cigarette classification method which is clear in logic, simple in steps, safe, effective, reliable and simple and convenient to operate, and can effectively predict the demand of each module in the next production cycle according to the historical data of cigarette sales.
Based on the above purposes, the technical scheme provided by the invention is as follows:
a cigarette classification method comprises the following steps:
s1, acquiring and summarizing historical data of all production batches of cigarettes in the previous production period;
s2, selecting an ith quality gauge, and acquiring the number of modules of the ith quality gauge and the weight of the input tobacco lamina from the historical data;
s3, acquiring weight ratio corresponding to each module in the ith standard according to the number of the modules and the weight of the tobacco lamina to be put;
s4, sorting the weight ratios corresponding to the modules in the ith standard gauge according to a preset rule to generate a standard formula of the ith standard gauge;
s5, repeating the steps S2 to S4 until standard formulas of all specifications are obtained;
s6, classifying all the specifications according to the standard formulas of all the specifications, the classified modules in all the specifications and the corresponding weight ratios in combination with a preset algorithm to generate a formula platform;
and S7, acquiring the demand of each module in the next production period according to the formula platform and the product specification demand in the preset next production period.
Preferably, the step S2 specifically includes:
A1. selecting an ith product gauge from all production batches of cigarettes;
A2. acquiring the total consumption amount and the weight of the input tobacco lamina in each module in the ith specification from the historical data;
A3. and summarizing the total consumption of each module, and acquiring the number of the modules of the ith specification.
Preferably, the step S3 specifically includes:
and respectively comparing the total consumption amount of each module in the ith quality gauge with the weight of the tobacco flakes put into the ith quality gauge, and acquiring the corresponding weight ratio in the ith quality gauge.
Preferably, the step S4 specifically includes:
the preset rule is descending order;
and sequencing the weight ratios corresponding to all modules in the ith specification from large to small to generate a standard formula of the ith specification.
Preferably, the step S6 specifically includes:
B1. constructing a tobacco leaf formula matrix according to the standard formulas of all the specifications;
B2. taking each module which is classified in all the specifications and the corresponding weight ratio as the attribute of the tobacco leaf formula matrix to obtain the tobacco leaf formula matrix value;
B3. and searching a standard gauge meeting a preset standard according to the tobacco leaf formula matrix value by combining a preset clustering algorithm, classifying the standard gauge meeting the preset standard and the standard formula gauge, and generating a plurality of formula platforms.
Preferably, the step S7 specifically includes:
C1. acquiring the quantity relation between modules in the formula platform and the formula specifications according to a plurality of formula platforms and the specification demand in the preset next production period;
C2. and acquiring the demand of each module in the next production period according to the quantity relation between the modules in the formula platform and the formula specification.
A cigarette sorting system comprising:
the historical data module is used for acquiring and summarizing historical data of all production batches of cigarettes in the past production period;
the parameter extraction module is used for selecting the ith cigarette specification in the cigarette and acquiring the module number of the ith cigarette specification and the weight of the input tobacco lamina from historical data;
the calculating module is used for calculating and obtaining the weight ratio corresponding to each module in the ith quality gauge according to the number of the modules of the ith quality gauge and the weight of the tobacco lamina input;
the sorting module is used for sorting the weight ratios corresponding to all modules in the ith specification according to a preset rule to generate a standard formula of the ith specification;
the classification module is used for classifying all the product gauges according to the standard formulas of all the product gauges, the classified modules in all the product gauges and the corresponding weight ratios in combination with a preset algorithm to generate a formula platform;
and the purchasing module is used for acquiring the demand of each module in the next production period according to the formula platform and the product specification demand in the preset next production period.
The invention provides a cigarette classification method, which comprises seven steps, wherein historical data of all production batches of cigarettes in the previous period are obtained and summarized; then selecting a standard, and acquiring the number of modules of the standard and the weight of the input tobacco lamina from historical data; calculating the weight ratio of each module of the standard according to the number of modules and the weight of the fed tobacco flakes; sorting the calculated weight ratios of the modules of the finished gauge according to a preset rule to generate a standard formula of the finished gauge; repeating the two steps until all standard formulas of all specifications are obtained; classifying all the product specifications according to the standard formulas of all the product specifications, the classified modules in all the product specifications and the corresponding weight ratios and combining with a preset algorithm to generate a formula platform; and calculating and acquiring the demand of each module in the next production cycle according to the formula platform and the product specification demand in the preset downward movement cycle. The method comprises the steps of obtaining and summarizing vertical data of all production batches of cigarettes in the previous production period, selecting one specification from the production batches, obtaining the number of modules of the specification and the weight of tobacco strips put into the specification from historical data, and calculating the weight ratio of each module in the specification according to the number of modules and the weight of the tobacco strips put into the tobacco strips; the weight ratio of the modules is sequenced according to a preset rule to generate a standard formula of the product specification; repeatedly selecting another standard gauge from the production batch, and continuously obtaining the standard formula of the other standard gauge until the standard formulas of all the standard gauges are obtained; classifying all the product specifications according to standard formulas of all the product specifications, each module classified in all the product specifications and the weight ratio of each module, and combining a preset algorithm, thereby generating a formula platform; and calculating and acquiring the demand of each module in the next production period according to the formula platform and the product specification demand in the preset next production period so as to purchase and prepare in advance. The invention can acquire the demand of each module in the next production cycle according to the historical data, can be used for guiding the purchase plan of the cigarette factory, effectively ensures the dynamic balance of the stock raw materials and supports the reasonable use of the product formula.
The invention also provides a cigarette classification system, which corresponds to the steps of the method one by one and has the same beneficial effects, and the details are not repeated herein.
Drawings
In order to more clearly illustrate the embodiments of the present application 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 application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a method of sorting cigarettes provided by an embodiment of the present invention;
fig. 2 is a flowchart of step S2 according to an embodiment of the present invention;
FIG. 3 is a flowchart of step S6 provided in the embodiment of the present invention;
fig. 4 is a flowchart of step S7 according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a similarity matrix of a constructed tobacco leaf group formula provided in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious 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.
Embodiments of the present invention are written in a progressive manner.
The embodiment of the invention provides a cigarette classification method. The technical problems that in the prior art, balance rationality of tobacco leaf purchasing and using is insufficient, a corresponding purchasing plan has no scientific basis, dynamic balance of stored raw materials is difficult to achieve, a product formula is unreasonable to use and the like are mainly solved.
A cigarette classification method comprises the following steps:
s1, acquiring and summarizing historical data of all production batches of cigarettes in the previous production period;
s2, selecting an ith standard gauge, and acquiring the number of modules of the ith standard gauge and the weight of the input tobacco lamina from historical data;
s3, acquiring weight ratio corresponding to each module in the ith standard according to the number of the modules and the weight of the tobacco lamina;
s4, sorting the weight ratios corresponding to all modules in the ith specification according to a preset rule to generate a standard formula of the ith specification;
s5, repeating the steps S2 to S4 until standard formulas of all specifications are obtained;
s6, classifying all the product gauges according to standard formulas of all the product gauges, all the modules classified in all the product gauges and corresponding weight ratios and combining with a preset algorithm to generate a formula platform;
and S7, acquiring the demand of each module in the next production cycle according to the formula platform and the product specification demand in the preset next production cycle.
Step S1, sorting and summarizing historical data of all production batches of cigarettes in the previous production period; in this embodiment, a total of 46 production data of all batches of the yellow crane building brand in a certain year is selected by a certain enterprise (in this embodiment, it is assumed that one production cycle is one year);
in step S2, in this embodiment, one of the 46 specifications is selected, and the total consumption data of each module in the specification and the total weight of the tobacco lamina modules put into the specification are obtained by searching production data;
in the step S3, calculating and obtaining the proportion of each module in the product gauge according to the total consumption data of each module in the product gauge and the total weight of the tobacco lamina modules put into the product gauge;
step S4, sorting the weight ratios of the modules of the standard gauge according to a preset sorting rule so as to generate a standard formula of the standard gauge;
in the step S5, repeating the step S2 to select another standard gauge until the step S4 generates a standard formula of the other standard gauge until the standard formulas of all the standard gauges are obtained;
in step S6, classifying all the product gauges according to the obtained standard formulas of all the product gauges, the classified modules in all the product gauges (classifying the modules in advance) and the corresponding weight ratios by combining a preset algorithm to generate a formula platform;
in step S7, the demand of each module in the next production period is calculated and obtained according to the obtained formula platform and the medium-specification demand (reasonably set according to practical factors such as the scale of actual manufacturers) in the next production period, so that the purchasing department can make a purchasing plan.
Preferably, step S2 is specifically:
A1. selecting an ith product gauge from all production batches of cigarettes;
A2. acquiring the total consumption amount and the weight of the input tobacco lamina of each module in the ith specification from historical data;
A3. and summarizing the total consumption of each module, and acquiring the number of the modules of the ith specification.
In step A1, in this embodiment, one grade gauge is selected from 46 grade gauges in all batches of yellow crane building brands in a certain year; the selection is not of special significance, the standard formula of the product gauge is obtained through the selected product gauge, and the standard formula of all the product gauges can be obtained by repeatedly selecting different product gauges;
in the step A2, the total consumption amount and the weight of the input tobacco lamina of each module in the product specification are inquired and obtained from historical data;
in the step A3, summarizing the total consumption of each module so as to obtain the number M of the modules of the product gauge;
in this embodiment, the formula for obtaining the total consumption amount of the modules in the specification is specifically:
wherein, weight ijm Standard for good i All K in j j Total consumption of mth module of lot; k j Total number of production batches in j years; q. q.s ijkm Standard for good i Weight of the tobacco lamina module m put in the kth batch of j years.
Preferably, step S3 is specifically:
and respectively comparing the total consumption amount of each module in the ith quality gauge with the weight of the tobacco flakes put into the ith quality gauge, and acquiring the corresponding weight ratio in the ith quality gauge.
In the actual application process, all modules used in the conventional product rule production are integrated through all historical production data, a standard value is provided for the construction of a formula platform, and the formula platform is combined with the structural layout of the whole cigarette product from two dimensions of the transverse dimension and the longitudinal dimension.
In this embodiment, the formula for obtaining the weight ratio corresponding to the ith specification is specifically:
wherein Q is ij Is sku i All K in j j The total weight of S tobacco sheet modules put into each batch; k is j Total number of production batches in j years; s is the total number of modules; q. q.s ijkm Standard for good i Weight of the tobacco lamina module m dropped into the kth batch in j years; ratio(s) ijkm Is sku i The proportion of module m in the formulation of the kth batch in j years is 0 if there is no module m.
Wherein stand _ ratio ijm Is sku i Sku occupied by mth module in j year i The proportion of all module weights used in j years; weight ijm Good rule sku i All K in j j Total consumption of mth module of batch; q ij Is sku i All K in j j Total weight of S tobacco lamina modules put into each batch.
Preferably, step S4 is specifically:
presetting a rule as descending order;
and (4) sorting the corresponding weight ratios of all modules in the ith specification from large to small to generate a standard formula of the ith specification.
In the actual application process, the types and the proportion differences of the modules used by different product gauges are mined according to different standard formulas of different product gauges. For convenience of calculation, the preset rule may be set to be a descending order, and the standard formula of the finished gauge is generated by sorting the weight ratios corresponding to the modules in a certain finished gauge, where the finished gauge a7220 is taken as an example, the standard formula of the finished gauge a7220 is shown in the following table 1 (partially truncated):
TABLE 1 Standard formulation of article size A7220
Preferably, step S6 is specifically:
B1. constructing a tobacco leaf formula matrix according to standard formulas of all specifications;
B2. taking each module which is graded in all the product specifications and the corresponding weight ratio as the attribute of the tobacco leaf formula matrix to obtain the tobacco leaf formula matrix value;
B3. and searching for the standard gauge meeting the preset standard according to the tobacco formula matrix value by combining a preset clustering algorithm, and classifying the standard gauge meeting the preset standard and the standard formula gauge to generate a plurality of formula platforms.
In the steps B1 and B2, according to the standard formulas of all specifications, a tobacco formula matrix can be constructed; in this example, a matrix M of n × M dimensions is obtained from all standard recipes nm Each row representing a cigarette gauge sku i Each column representing each module m Using the ratio of the use weight of all history modules in the cigarette product gauge as an attribute to feature ijm Standard formula standard specification i Percentage of m-th module in j years, feature ijm ＝stand_ratio ijm (ii) a Each row is a feature vector for each sku, and each column represents an attribute, i.e., each column represents a module. M is a group of nm The value of (a) represents the historical usage of the mth module in the nth cigarette gauge. Matrix M nm As shown in FIG. 5, a similarity matrix of the tobacco group formula is constructed from the dimension of module proportion, so that the module composition of the cigarette product specification is the basis of cigarette classification.
In the actual application process, all the product specifications and formulas of the same category are integrated into a formula platform again according to the classified product specifications, and the product specifications in the same category share one formula platform, so that the decision cost of module purchase is reduced;
and in the step B3, according to the standard formulas of different specifications, finding out specifications with similar standard formulas through clustering, and classifying the specifications into one class. Classifying the grade by three unsupervised clustering methods (K-means, SOM and GMM) of machine learning to obtain a result. The cigarette product specifications are clustered, and the purpose is to classify similar products into one class, so that the same class of cigarettes can be regarded as a formula platform when cigarette raw materials are purchased, and the decision of raw material purchasing is simplified. In clustering, if the number of categories is too small, the difference between the specifications is easily ignored, and if the number of categories is set to be too large, the difference between the specifications may be enlarged. Thus, in combination with the actual conditions of the product specifications, and taking into account the requirements of the actual classification of the cigarette products, the number of categories is defined herein as five, 5, 6, 7, 8 and 9, with the results shown in table 2:
TABLE 2 clustering results
Preferably, step S7 is specifically:
C1. acquiring the quantity relation between modules in the formula platform and the formula specification according to the quantity demands of the plurality of formula platforms and the preset specification in the next production period;
C2. and acquiring the demand of each module in the next production cycle according to the quantity relationship between the modules in the formula platform and the formula specification.
In the actual application process, the module demand of the next production plan period is decided according to the clustered module categories, and data support is provided for module purchasing decision
In the steps C1 and C2, module purchasing is to calculate the total weight of each module according to the demand of the formula platform and the next production period specification, and further calculate the purchasing quantity of the raw tobacco according to the quantity relation between the formula modules and the raw tobacco, wherein the specific calculation process is as follows:
wherein, weight i(j+1)m Good rule sku i All K in j +1 year j Total consumption of mth module of batch in G categories; demand i(j+1) Standard for good i Demand in year j +1, stand _ ratio ijm Is sku i Sku occupied by mth module in j year i The proportion of all module weights used in j; sku ig Is sku i The class discrimination value of the previous production cycle,
a cigarette sorting system comprising:
the historical data module is used for acquiring and summarizing historical data of all production batches of cigarettes in the past production period;
the parameter extraction module is used for selecting the ith cigarette specification in the cigarette and acquiring the module number of the ith cigarette specification and the weight of the input tobacco lamina from historical data;
the calculating module is used for calculating and obtaining the weight ratio corresponding to each module in the ith specification according to the number of the modules of the ith specification and the weight of the tobacco lamina;
the sorting module is used for sorting the weight ratios corresponding to all modules in the ith specification according to a preset rule to generate a standard formula of the ith specification;
the classification module is used for classifying all the product gauges according to the standard formulas of all the product gauges, the classified modules in all the product gauges and the corresponding weight ratios in combination with a preset algorithm to generate a formula platform;
and the purchasing module is used for acquiring the demand of each module in the next production period according to the formula platform and the product specification demand in the preset next production period.
In the actual application process, the cigarette classification system comprises a historical data module, a parameter extraction module, a calculation module, a sorting module, a classification module and a purchasing module; in the working process, a historical data module user acquires and summarizes historical data of all production batches of cigarettes in the past production period and sends the historical data to a parameter extraction module; the parameter extraction module selects the ith cigarette specification in the cigarette, acquires the module number and the input cigarette weight of the ith cigarette specification from historical data, and sends the module number and the input cigarette weight of the ith cigarette specification to the calculation module; the calculating module calculates and obtains the weight ratio corresponding to each module in the ith standard according to the number of the modules of the ith standard and the weight of the tobacco lamina, and sends the weight ratio corresponding to each module in the ith standard to the sorting module; the sorting module sorts the weight ratios corresponding to all modules in the ith specification according to a preset rule in advance to generate a standard formula of the ith specification; acquiring standard formulas of all the product specifications under the combined action of the parameter extraction module, the calculation module and the sorting module, and sending the standard formulas of all the product specifications to the classification module; the classification module classifies all the product specifications according to standard formulas of all the product specifications, all the modules classified in all the product specifications and corresponding weight ratios in combination with a preset algorithm, a formula platform is generated and sent to the purchasing module, and the purchasing module acquires the demand of each module in the next production cycle according to the formula platform and the product specification demand preset in the next production cycle.
In the embodiments provided in the present application, it should be understood that the disclosed method and apparatus may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the modules is only one division of logical functions, and other divisions may be realized in practice, such as: multiple modules or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or modules may be electrical, mechanical or other.
In addition, all functional modules in the embodiments of the present invention may be integrated into one processor, or each module may be separately used as one device, or two or more modules may be integrated into one device; each functional module in each embodiment of the present invention may be implemented in the form of hardware, or in the form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps of implementing the method embodiments may be implemented by program instructions and related hardware, where the program instructions may be stored in a computer-readable storage medium, and when executed, the program instructions perform the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as a removable Memory device, a Read Only Memory (ROM), a magnetic disk, or an optical disk.
It should be understood that the use of "system," "device," "unit," and/or "module" herein is merely one way to distinguish between different components, elements, components, parts, or assemblies of different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.
As used in this application and in the claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to include the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements. An element defined by the phrase "comprising a component of ' 8230 ' \8230; ' does not exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.
If used in this application, the flowcharts are intended to illustrate operations performed by the system according to embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the various steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to or removed from these processes.
It is also noted that, in this document, terms such as "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that an article or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such article or apparatus. Without further limitation, an element defined by the phrases "comprising one of the elements 8230 \8230;" does not exclude the presence of additional like elements in an article or device comprising the same element.
The cigarette classification method and system provided by the invention are introduced in detail above. The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (7)
1. A cigarette classification method is characterized by comprising the following steps:
s1, acquiring and summarizing historical data of all production batches of cigarettes in the previous production period;
s2, selecting an ith quality gauge, and acquiring the number of modules of the ith quality gauge and the weight of the input tobacco lamina from the historical data;
s3, acquiring weight ratio corresponding to each module in the ith standard according to the number of the modules and the weight of the tobacco lamina to be put;
s4, sorting the weight ratios corresponding to the modules in the ith standard gauge according to a preset rule to generate a standard formula of the ith standard gauge;
s5, repeating the steps S2 to S4 until standard formulas of all specifications are obtained;
s6, classifying all the product gauges according to the standard formula of all the product gauges, the classified modules in all the product gauges and the corresponding weight ratios in combination with a preset algorithm to generate a formula platform;
and S7, acquiring the demand of each module in the next production period according to the formula platform and the product specification demand in the preset next production period.
2. The cigarette classification method according to claim 1, wherein the step S2 is specifically:
A1. selecting an ith product gauge from all production batches of cigarettes;
A2. acquiring the total consumption amount and the weight of the input tobacco lamina of each module in the ith specification from the historical data;
A3. and summarizing the total consumption of each module, and acquiring the number of the modules of the ith specification.
3. The cigarette classification method according to claim 2, wherein the step S3 is specifically:
and respectively comparing the total consumption amount of each module in the ith quality gauge with the weight of the tobacco flakes put into the ith quality gauge, and acquiring the corresponding weight ratio in the ith quality gauge.
4. The cigarette classification method according to claim 3, wherein the step S4 is specifically:
the preset rule is descending order;
and sequencing the weight ratio corresponding to each module in the ith standard gauge from large to small to generate a standard formula of the ith standard gauge.
5. The cigarette classification method according to claim 4, wherein the step S6 specifically comprises:
B1. constructing a tobacco leaf formula matrix according to the standard formulas of all the specifications;
B2. taking each module which is graded in all the specifications and the corresponding weight ratio as the attribute of the tobacco leaf formula matrix to obtain the tobacco leaf formula matrix value;
B3. and searching a standard gauge meeting a preset standard according to the tobacco leaf formula matrix value by combining a preset clustering algorithm, classifying the standard gauge meeting the preset standard and the standard formula gauge, and generating a plurality of formula platforms.
6. The cigarette classification method according to claim 1, wherein the step S7 is specifically:
C1. acquiring the quantity relation between modules in the formula platform and the formula specifications according to a plurality of formula platforms and the specification demand in the preset next production period;
C2. and acquiring the demand of each module in the next production period according to the quantity relation between the modules in the formula platform and the formula specification.
7. A cigarette sorting system, comprising:
the historical data module is used for acquiring and summarizing historical data of all production batches of cigarettes in the past production period;
the parameter extraction module is used for selecting the ith cigarette specification in the cigarette, and acquiring the module number of the ith cigarette specification and the weight of the input tobacco lamina from historical data;
the calculating module is used for calculating and obtaining the weight ratio corresponding to each module in the ith quality gauge according to the number of the modules of the ith quality gauge and the weight of the tobacco lamina input;
the sorting module is used for sorting the weight ratios corresponding to all modules in the ith specification according to a preset rule to generate a standard formula of the ith specification;
the classification module is used for classifying all the product gauges according to the standard formulas of all the product gauges, the classified modules in all the product gauges and the corresponding weight ratios in combination with a preset algorithm to generate a formula platform;
and the purchasing module is used for acquiring the demand of each module in the next production period according to the formula platform and the product specification demand in the preset next production period.
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| CN202210985523.0A CN115345487A (en) | 2022-08-15 | 2022-08-15 | Cigarette classification method and system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117932490A (en) * | 2024-01-17 | 2024-04-26 | 江苏软擎信息科技有限公司 | Recipe classification method, system, electronic equipment and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117932490A (en) * | 2024-01-17 | 2024-04-26 | 江苏软擎信息科技有限公司 | Recipe classification method, system, electronic equipment and storage medium |
| CN117932490B (en) * | 2024-01-17 | 2024-07-16 | 一半科技(江苏)有限公司 | Recipe classification method, system, electronic equipment and storage medium |
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