CN116882615A - Quality evaluation index quantification method for cut tobacco storage process - Google Patents

Quality evaluation index quantification method for cut tobacco storage process Download PDF

Info

Publication number
CN116882615A
CN116882615A CN202310692539.7A CN202310692539A CN116882615A CN 116882615 A CN116882615 A CN 116882615A CN 202310692539 A CN202310692539 A CN 202310692539A CN 116882615 A CN116882615 A CN 116882615A
Authority
CN
China
Prior art keywords
moisture
deviation
standard deviation
storage process
value
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202310692539.7A
Other languages
Chinese (zh)
Inventor
刘继辉
杨晶津
余晓宇
马晓龙
曹喆
吴昊
和金
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hongyun Honghe Tobacco Group Co Ltd
Original Assignee
Hongyun Honghe Tobacco Group Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hongyun Honghe Tobacco Group Co Ltd filed Critical Hongyun Honghe Tobacco Group Co Ltd
Priority to CN202310692539.7A priority Critical patent/CN116882615A/en
Publication of CN116882615A publication Critical patent/CN116882615A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • AHUMAN NECESSITIES
    • A24TOBACCO; CIGARS; CIGARETTES; SIMULATED SMOKING DEVICES; SMOKERS' REQUISITES
    • A24BMANUFACTURE OR PREPARATION OF TOBACCO FOR SMOKING OR CHEWING; TOBACCO; SNUFF
    • A24B9/00Control of the moisture content of tobacco products, e.g. cigars, cigarettes, pipe tobacco
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/18Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04Manufacturing
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30Computing systems specially adapted for manufacturing

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Human Resources & Organizations (AREA)
  • Theoretical Computer Science (AREA)
  • Economics (AREA)
  • Data Mining & Analysis (AREA)
  • Strategic Management (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Mathematical Physics (AREA)
  • Tourism & Hospitality (AREA)
  • Marketing (AREA)
  • General Business, Economics & Management (AREA)
  • Pure & Applied Mathematics (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Operations Research (AREA)
  • Computational Mathematics (AREA)
  • Development Economics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Manufacturing & Machinery (AREA)
  • Probability & Statistics with Applications (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Health & Medical Sciences (AREA)
  • Educational Administration (AREA)
  • Evolutionary Biology (AREA)
  • Manufacture Of Tobacco Products (AREA)
  • Primary Health Care (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Game Theory and Decision Science (AREA)
  • Algebra (AREA)
  • Quality & Reliability (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • General Health & Medical Sciences (AREA)

Abstract

The invention discloses a quality evaluation index quantification method in a cut tobacco storage process. Specifically, a regression equation is fitted to the water content deviation before the storage process starts and the historical data of the water deviation correcting capability of the storage process, the expected value of the water deviation correcting capability is calculated according to the fitting relation and the known water content deviation before the storage process starts, and the actual value of the water deviation correcting capability is compared with the expected value, so that the quantitative index for evaluating the water deviation correcting capability can be obtained. The invention provides a more visual and accurate quality evaluation strategy for the storage procedure in the cigarette processing process, and can objectively evaluate the capacity of balancing the water content of the storage procedure according to the water deviation correction capacity index of the storage procedure, thereby effectively checking and improving the rationality of the parameters of the storage procedure.

Description

Quality evaluation index quantification method for cut tobacco storage process
Technical Field
The invention relates to the field of cigarette manufacturing, in particular to a quantification method for quality evaluation indexes in a cut tobacco storage process.
Background
In the cigarette processing process, different products are provided with corresponding leaf group formulas, and the leaf group formulas are composed of raw tobacco leaves of different varieties and grades according to a specified feeding sequence. In the actual production process, the water content and the color of raw tobacco leaves of different varieties and grades are generally different, so that the fluctuation of the water content of raw materials in each production batch is large, the stable regulation and control of parameters of cigarette processing equipment are not facilitated, the accurate control of the water content of subsequent processing procedures of cigarettes is not facilitated, and the difference of the quality of cigarette products in batches is easily increased.
In order to gradually reduce the fluctuation of the water content in the subsequent cigarette processing procedure, reduce the intra-batch variability, the tobacco leaf feeding and water supplementing procedures are generally followed by the tobacco leaf storing procedure, the tobacco leaf storing procedure is followed by the tobacco shred flavoring, the tobacco leaf storing procedure and the tobacco shred storing procedure are summarized as the storing procedure, the storing procedure must be arranged in a constant temperature and humidity environment, the storing time is determined by specific product design, the water content and the temperature of the tobacco leaf and the tobacco shred can be balanced when the required storing time is reached, the fluctuation of the water content in the subsequent cigarette processing procedure is reduced, and the stability of the quality of the product in the batch is increased.
The existing quality evaluation method for the tobacco leaf and tobacco shred storage process is to check whether the storage time meets the product design requirement or not, so that whether the tobacco leaf and tobacco shred are subjected to the storage process or not is judged, the storage time is wide in design range, the capacity of balancing the water content of the storage process in the storage time cannot be intuitively and accurately evaluated, the difference between batches of the storage process cannot be objectively compared and analyzed, and accurate guidance is difficult to be provided for setting the storage time and the temperature and humidity of the storage environment.
Disclosure of Invention
In view of the foregoing, the present invention aims to provide a method for quantifying quality evaluation indexes in a cut tobacco storage process, so as to solve the aforementioned technical problems.
The technical scheme adopted by the invention is as follows:
the invention provides a quality evaluation index quantification method for a cut tobacco storage process, which comprises the following steps:
acquiring a first standard deviation of the water content before the cut tobacco storage process begins and a second standard deviation of the water content after the cut tobacco storage process is finished;
acquiring a moisture deviation correcting capacity value of a storage procedure by using the first standard deviation and the second standard deviation;
fitting by utilizing the first standard deviation and the historical data of the moisture deviation correcting capability value to obtain a fitting regression equation representing the fitting relation between the first standard deviation and the moisture deviation correcting capability value;
according to the fitting regression equation and the standard deviation actual value of the water content before the current cut tobacco storage procedure starts, obtaining the water deviation correcting capacity expected value of the current cut tobacco storage procedure;
and obtaining a moisture deviation rectifying capability evaluation score aiming at the current cut tobacco storage procedure according to a comparison result of the actual moisture deviation rectifying capability value of the current cut tobacco storage procedure and the expected moisture deviation rectifying capability value.
In at least one possible implementation thereof, the moisture correction capability value = the first standard deviation ∈the second standard deviation.
In at least one possible implementation manner, the fitting relation comprises any one of the following: linear, power function, logarithmic function, exponential function, polynomial function.
In at least one possible implementation manner, the actual value of the moisture deviation correcting capability is obtained by using the actual value of the standard deviation of the moisture content before the current cut tobacco storage procedure starts and the actual value of the standard deviation of the moisture content after the current cut tobacco storage procedure is finished.
In at least one possible implementation, the moisture correction capability evaluation score=the actual moisture correction capability value ∈the desired moisture correction capability value.
In at least one possible implementation manner, if the moisture deviation rectifying capability evaluation score exceeds a preset full score, the final moisture deviation rectifying capability evaluation score is equal to the full score; and if the moisture deviation correcting capability evaluation score is smaller than the full score, the final moisture deviation correcting capability evaluation score is equal to the actual score calculation result.
Compared with the prior art, the main design concept of the invention is that the water content standard deviation before the storage process is started and the water content standard deviation after the storage process is finished are analyzed by comparing the historical data, and an evaluation mechanism of the water deviation correcting capability is introduced, so that the capability of balancing the water content in the storage process is objectively evaluated. Because the water content standard deviation before the storage process is started has certain batch-to-batch variability and has certain influence on the water deviation correcting capability result, batch-to-batch comparison analysis is provided for the water deviation correcting capability of the storage process, specifically, a regression equation is fitted to the water content standard deviation before the storage process is started and the historical data of the water deviation correcting capability of the storage process, the expected value of the water deviation correcting capability is calculated according to the fitting relation and the known water content standard deviation before the storage process is started, the actual value of the water deviation correcting capability is compared with the expected value, and the evaluation score of the water deviation correcting capability can be obtained, so that whether the water content balancing capability of the storage process reaches the expected level can be effectively evaluated. The invention provides a more visual and accurate quality evaluation strategy for the storage procedure in the same-standard cigarette processing process of the factory, and can objectively evaluate the capacity of balancing the water content of the storage procedure according to the water deviation correcting capacity of the storage procedure, thereby effectively checking and improving the rationality of parameters such as the storage time of the storage procedure, the temperature and humidity of the storage environment and the like.
The invention effectively reduces the regulating pressure of the stability of the water content of the tobacco leaves in the leaf processing section in the cigarette processing process, improves the precise control capability of the water content of cut tobacco shreds, provides front-end guarantee for the stable control of the water content of the leaf shred processing section, can provide reference data for the precise setting of parameters such as the storage time of the tobacco leaves and tobacco shreds storage procedure, the temperature and humidity of the storage environment and the like, and further improves the precise control level of the cigarette processing technology.
Drawings
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described with reference to the accompanying drawings, in which:
fig. 1 is a flow chart of a method for quantifying a quality evaluation index in a cut tobacco storage process according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.
The invention provides an embodiment of a quality evaluation index quantification method in a cut tobacco storage process, specifically, as shown in fig. 1, the method comprises the following steps:
step S1, acquiring a first standard deviation of the water content before the cut tobacco storage process begins and a second standard deviation of the water content after the cut tobacco storage process is finished;
s2, acquiring a moisture deviation correcting capacity value of a storage procedure by using the first standard deviation and the second standard deviation;
specifically, the obtaining the moisture correction capability value of the storage process includes: setting a first standard deviation as x (the historical value and the actual value mentioned later are represented by x), and a second standard deviation as y (the actual value mentioned later is also represented by y), wherein the moisture deviation correcting capacity value (the historical value and the actual value mentioned later are represented by z) is z, and then the moisture deviation correcting capacity value is obtained according to the following formula:
z=x/y (1)
step S3, fitting is carried out by utilizing the first standard deviation and the historical data of the moisture deviation correcting capability value, and a fitting regression equation representing the fitting relation between the first standard deviation and the moisture deviation correcting capability value is obtained;
in actual operation, the fit relationship includes any one of the following: linear, power function, logarithmic function, exponential function, polynomial function.
S4, according to the fitting regression equation and the standard deviation actual value of the water content before the current cut tobacco storage procedure starts, obtaining the water deviation correcting capacity expected value of the current cut tobacco storage procedure;
the following examples are used to describe the fitting analysis of historical data of moisture content bias x and moisture correction capability z before the beginning of different storage procedures for a brand produced by a factory, using, but not limited to, rstudio software, for example, as follows:
(1) And (3) carrying out fitting analysis on the historical data of x and z in the storage procedure A, wherein a linear relation exists and a corresponding fitting linear regression equation is obtained, and the method is as follows:
z=16.565x+0.37384
according to the linear regression equation, when the water content standard deviation x before the start of the storage process is known, the expected value z of the water deviation correcting capability of the storage process can be calculated 0 The formula is calculated:
z 0 =16.565x+0.37384
(2) In the storage procedure B, the historical data of x and z are subjected to fitting analysis, a power function nonlinear relation exists, and a power function fitting equation is obtained as follows;
z=9.81×x 3.11 +1.156
according to the power function regression equation, when the water content standard deviation x before the storage procedure starts is known, the expected value z of the water deviation correcting capability of the storage procedure can be calculated 0 The formula is calculated:
z 0 =9.81×x 3.11 +1.156
(3) C, carrying out fitting analysis on historical data of x and z in the storage procedure, wherein a logarithmic function nonlinear relation exists, and a logarithmic function fitting equation is obtained as follows;
z=4.9881ln x+12.02
according to this logarithmic functionThe equation is returned, when the water content standard deviation x is known before the storage procedure starts, the expected value z of the water deviation correcting capability of the storage procedure can be calculated 0 The formula is calculated:
z 0 =4.9881ln x+12.02
(4) D, carrying out fitting analysis on historical data of x and z in the storage procedure, wherein an exponential function nonlinear relation exists, and an exponential function fitting equation is obtained as follows;
z=11.817/(1+e 6.217-10.42X )+1.06
according to the regression equation of the index function, when the water content standard deviation x before the storage process is started is known, the expected value z of the water deviation correcting capability of the storage process can be calculated 0 The formula is calculated:
z 0 =11.817/(1+e 6.217-10.42X )+1.06
(5) The historical data of x and z in the E storage procedure are subjected to fitting analysis, a polynomial function nonlinear relation exists, and a polynomial function fitting equation is obtained as follows;
z=31.185X 3 -58.905X 2 +37.62X+0.0468
according to the polynomial function regression equation, when the water content standard deviation x before the storage procedure is started is known, the expected value z of the water deviation correcting capability of the storage procedure can be calculated 0 The formula is calculated:
z 0 =31.185X 3 -58.905X 2 +37.62X+0.0468
and step S5, obtaining the evaluation score of the moisture deviation rectifying capability aiming at the current cut tobacco storage procedure according to the comparison result of the actual value of the moisture deviation rectifying capability of the current cut tobacco storage procedure and the expected value of the moisture deviation rectifying capability.
Specifically, the actual value of the moisture correction capability mentioned herein may be calculated with reference to the foregoing formula (1), that is:
and acquiring the actual value of the moisture deviation correcting capability of the current cut tobacco storage procedure by using the actual value of the standard deviation of the moisture content before the current cut tobacco storage procedure starts and the actual value of the standard deviation of the moisture content after the current cut tobacco storage procedure is finished.
The specific characterization mode of the moisture deviation correcting capability evaluation score W can refer to the following calculation formula:
in this embodiment, W may be represented in terms of percentages, based on this example, if the moisture correction capability evaluation score W >100 after calculation, the final moisture correction capability evaluation score is determined to be full (evaluation score=100); if W is less than or equal to 100, determining the final water deviation rectifying capability evaluation score as an actual calculation result. It will of course be appreciated that in other embodiments the system may not be limited to a percentage.
In summary, the main design concept of the present invention is to analyze the standard deviation of the water content before the storage process starts and the standard deviation of the water content after the storage process is completed by comparing the historical data, and introduce an evaluation mechanism for the water deviation correcting capability, so as to objectively evaluate the capability of balancing the water content in the storage process. Because the water content standard deviation before the storage process is started has certain batch-to-batch variability and has certain influence on the water deviation correcting capability result, batch-to-batch comparison analysis is provided for the water deviation correcting capability of the storage process, specifically, a regression equation is fitted to the water content standard deviation before the storage process is started and the historical data of the water deviation correcting capability of the storage process, the expected value of the water deviation correcting capability is calculated according to the fitting relation and the known water content standard deviation before the storage process is started, the actual value of the water deviation correcting capability is compared with the expected value, and the evaluation score of the water deviation correcting capability can be obtained, so that whether the water content balancing capability of the storage process reaches the expected level can be effectively evaluated. The invention provides a more visual and accurate quality evaluation strategy for the storage procedure in the same-standard cigarette processing process of the factory, and can objectively evaluate the capacity of balancing the water content of the storage procedure according to the water deviation correcting capacity of the storage procedure, thereby effectively checking and improving the rationality of parameters such as the storage time of the storage procedure, the temperature and humidity of the storage environment and the like.
In the embodiments of the present invention, "at least one" means one or more, and "a plurality" means two or more. "and/or", describes an association relation of association objects, and indicates that there may be three kinds of relations, for example, a and/or B, and may indicate that a alone exists, a and B together, and B alone exists. Wherein A, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of the following" and the like means any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c may represent: a, b, c, a and b, a and c, b and c or a and b and c, wherein a, b and c can be single or multiple.
The construction, features and effects of the present invention are described in detail according to the embodiments shown in the drawings, but the above is only a preferred embodiment of the present invention, and it should be understood that the technical features of the above embodiment and the preferred mode thereof can be reasonably combined and matched into various equivalent schemes by those skilled in the art without departing from or changing the design concept and technical effects of the present invention; therefore, the invention is not limited to the embodiments shown in the drawings, but is intended to be within the scope of the invention as long as changes made in the concept of the invention or modifications to the equivalent embodiments do not depart from the spirit of the invention as covered by the specification and drawings.

Claims (6)

1. A quality evaluation index quantification method for cut tobacco storage process is characterized by comprising the following steps:
acquiring a first standard deviation of the water content before the cut tobacco storage process begins and a second standard deviation of the water content after the cut tobacco storage process is finished;
acquiring a moisture deviation correcting capacity value of a storage procedure by using the first standard deviation and the second standard deviation;
fitting by utilizing the first standard deviation and the historical data of the moisture deviation correcting capability value to obtain a fitting regression equation representing the fitting relation between the first standard deviation and the moisture deviation correcting capability value;
according to the fitting regression equation and the standard deviation actual value of the water content before the current cut tobacco storage procedure starts, obtaining the water deviation correcting capacity expected value of the current cut tobacco storage procedure;
and obtaining a moisture deviation rectifying capability evaluation score aiming at the current cut tobacco storage procedure according to a comparison result of the actual moisture deviation rectifying capability value of the current cut tobacco storage procedure and the expected moisture deviation rectifying capability value.
2. The method for quantifying a quality evaluation index for a cut tobacco storage process according to claim 1, wherein the moisture correction capability value = the first standard deviation ∈ the second standard deviation.
3. The method for quantifying a quality evaluation index of a cut tobacco storage process according to claim 1, wherein the fitting relation comprises any one of the following: linear, power function, logarithmic function, exponential function, polynomial function.
4. The method according to claim 1, wherein the actual value of the moisture correction capability is obtained by using an actual value of a standard deviation of the moisture content before the start of the current cut-tobacco storage process and an actual value of the standard deviation of the moisture content after the completion of the current cut-tobacco storage process.
5. The method according to any one of claims 1 to 4, wherein the moisture correction capability evaluation score=the actual moisture correction capability value/the desired moisture correction capability value.
6. The method according to claim 5, wherein if the moisture deviation rectifying capability evaluation score exceeds a preset full score, the final moisture deviation rectifying capability evaluation score is equal to the full score; and if the moisture deviation correcting capability evaluation score is smaller than the full score, the final moisture deviation correcting capability evaluation score is equal to the actual score calculation result.
CN202310692539.7A 2023-06-12 2023-06-12 Quality evaluation index quantification method for cut tobacco storage process Pending CN116882615A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310692539.7A CN116882615A (en) 2023-06-12 2023-06-12 Quality evaluation index quantification method for cut tobacco storage process

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310692539.7A CN116882615A (en) 2023-06-12 2023-06-12 Quality evaluation index quantification method for cut tobacco storage process

Publications (1)

Publication Number Publication Date
CN116882615A true CN116882615A (en) 2023-10-13

Family

ID=88270592

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310692539.7A Pending CN116882615A (en) 2023-06-12 2023-06-12 Quality evaluation index quantification method for cut tobacco storage process

Country Status (1)

Country Link
CN (1) CN116882615A (en)

Similar Documents

Publication Publication Date Title
CN109602062B (en) Loose moisture regain self-adaptive water control method and system based on digital physical model
CN103844344B (en) A kind of regulate and control the method for different batches cigarette shreds quality uniformity and application thereof
US6061640A (en) Method of and apparatus for extracting abnormal factors in a processing operation
CN107038254B (en) Cigarette quality monitoring method and device
CN110196265B (en) Method for evaluating distribution stability of cut tobacco in cigarette branches in batch based on distribution probability
CN116933210B (en) Food processing filling equipment monitoring method and system based on multidimensional sensor
CN110876481B (en) Control method and device for tobacco shred drying parameters
CN116882615A (en) Quality evaluation index quantification method for cut tobacco storage process
CN115251445A (en) Method for controlling moisture content of tobacco leaves at outlet of loosening and conditioning machine
CN110973687A (en) Accurate control method for moisture in silk making process
CN110973686B (en) Method for establishing accurate moisture control model in silk making process
CN112003891B (en) Multi-sensing data fusion method for intelligent networked vehicle controller
CN113576016A (en) Shredding adjusting method based on tobacco shred structure
CN112126907A (en) Vacuum coating control system and control method thereof, and vacuum coating equipment
CN107274036B (en) Crop yield prediction method and system
CN114741258B (en) Big data-based computer performance control analysis system and method
CN115017700A (en) Cigarette shred making process variable selection and weighting method based on SCAD algorithm
CN113712245B (en) Cigarette circumference accurate control method
CN112205658B (en) Method for evaluating tobacco shred quality of cigarette production line
CN110866221B (en) Detection method for threshing and redrying data accuracy
CN113984708A (en) Maintenance method and device of chemical index detection model
CN110286663B (en) Regional cigarette physical index standardized production improving method
CN113970502A (en) Tobacco leaf water content prediction model construction method based on rapid oven method
CN112464389A (en) Determination method and determination device for air cooling temperature of working roll of rolling mill and electronic terminal
CN114324764A (en) Multi-dimensional evaluation method for product quality in cigarette shredding process based on material characteristic value

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination