CN109222220B

CN109222220B - Method and system for evaluating cigarette rolling quality index

Info

Publication number: CN109222220B
Application number: CN201811000753.7A
Authority: CN
Inventors: 曹琦; 吴永生; 邹甫; 林苗俏; 陈晓杜; 苏铃; 郭天文; 李汉瑞; 林慧; 黄启胜
Original assignee: Longyan Tobacco Industry Co Ltd
Current assignee: Longyan Tobacco Industry Co Ltd
Priority date: 2018-08-30
Filing date: 2018-08-30
Publication date: 2021-08-20
Anticipated expiration: 2038-08-30
Also published as: CN109222220A

Abstract

The invention provides a method and a system for evaluating cigarette rolling quality index, and relates to the field of data analysis in the tobacco industry. In the method, the deviation and the dispersion of the physical quality index are calculated based on the inspection data of each physical index of cigarette samples in a batch. And calculating to obtain the physical quality index according to the deviation and the dispersion of the physical quality index. And calculating the appearance quality index by a method of grading the appearance quality of the cigarette samples in the batch. And calculating according to the physical quality index and the appearance quality index to obtain the cigarette rolling quality index. The method and the device realize the evaluation of the cigarette rolling quality index.

Description

Method and system for evaluating cigarette rolling quality index

Technical Field

The disclosure relates to the field of data analysis in the tobacco industry, in particular to a method and a system for evaluating cigarette rolling quality index.

Background

Currently, in the tobacco industry, the evaluation of cigarette rolling quality index can provide an improved reference for subsequent production. In the related technology, the cigarette rolling quality index can be obtained by adopting a quality defect deduction method. However, the method is simple, and the scientific evaluation and analysis capability of the method on the cigarette rolling quality is limited.

Disclosure of Invention

One technical problem that this disclosed embodiment solved is: provides a method for evaluating cigarette rolling quality index.

According to an aspect of the disclosed embodiments, a method for evaluating a cigarette rolling quality index is provided, including: calculating the deviation and dispersion of the physical quality indexes based on the inspection data of each physical index of the cigarette samples in the batch; calculating according to the deviation and dispersion of the physical quality index to obtain a physical quality index; calculating an appearance quality index by a method of scoring the appearance quality of the cigarette samples in the batch; and calculating according to the physical quality index and the appearance quality index to obtain the cigarette rolling quality index.

In some embodiments, the inspection data of each physical index comprises inspection data of each physical index of self-inspection and inspection data of each physical index of special inspection; the step of calculating the deviation and dispersion of the physical quality index comprises the following steps: calculating the deviation and dispersion of the physical self-checking quality indexes of the cigarette products in the batch based on the checking data of each physical index of the self-checking of the cigarette samples in the batch; calculating the deviation and dispersion of the physical special inspection quality indexes of the cigarette products of the batch based on the inspection data of each physical index of the special inspection of the cigarette samples in the batch; and calculating the deviation of the physical quality index according to the deviation of the physical self-checking quality index and the deviation of the physical special-checking quality index, and calculating the dispersion of the physical quality index according to the dispersion of the physical self-checking quality index and the dispersion of the physical special-checking quality index.

In some embodiments, the step of calculating the deviation and dispersion of the quality indicator of the physical self-test comprises: calculating the deviation and dispersion of the single self-checking physical indexes of the cigarette products in the batch based on the checking data of the physical indexes of the self-checking of the cigarette samples in the batch; weighting and summing the deviation degrees of the single self-checking physical indexes to calculate the deviation degree of the physical self-checking quality indexes of the cigarette products in the batch; and calculating the dispersion of the physical self-checking quality index of the cigarette products in the batch based on the dispersion of the single self-checking physical index, wherein the dispersion of the physical self-checking quality index is obtained by weighted summation of the dispersion of the single self-checking physical index, or the square of the dispersion of the single self-checking physical index is calculated, each is weighted summation is carried out on the square of the dispersion of the single self-checking physical index, and then the value after weighted summation is squared to calculate the dispersion of the physical self-checking quality index.

In some embodiments, the step of calculating the deviation and dispersion of the physical expertise quality index comprises: calculating the deviation and dispersion of the single special physical indexes of the cigarette products in the batch based on the inspection data of the special physical indexes of the cigarette samples in the batch; weighting and summing the deviation degrees of the single-item special inspection physical indexes to calculate and obtain the deviation degree of the physical special inspection quality indexes of the cigarette products in the batch; and calculating to obtain the dispersion of the physical special inspection quality index of the cigarette products of the batch based on the dispersion of the single special inspection physical index, wherein the dispersion of the physical special inspection quality index is obtained by weighted summation of the dispersion of the single special inspection physical index, or the dispersion of the physical special inspection quality index is obtained by calculating each square of the dispersion of the single special inspection physical index, each square of the dispersion of the single special inspection physical index is weighted summation, and then the value after weighted summation is squared to calculate the dispersion of the physical special inspection quality index.

In some embodiments, the step of calculating the deviation of the physical quality indicator according to the deviation of the physical self-test quality indicator and the deviation of the physical special test quality indicator comprises: and weighting and summing the deviation of the physical self-inspection quality index and the deviation of the physical special-inspection quality index to calculate the deviation of the physical quality index.

In some embodiments, the step of calculating the dispersion of the physical quality indicator according to the dispersion of the physical self-test quality indicator and the dispersion of the physical special test quality indicator includes: carrying out weighted summation on the dispersion of the physical self-detection quality index and the dispersion of the physical special-detection quality index to calculate the dispersion of the physical quality index; or calculating the square of the dispersion of the physical self-inspection quality index and the square of the dispersion of the physical special inspection quality index, carrying out weighted summation on the square of the dispersion of the physical self-inspection quality index and the square of the dispersion of the physical special inspection quality index, and then squaring the value after weighted summation to calculate the dispersion of the physical quality index.

In some embodiments, the step of calculating the physical quality index according to the deviation and the dispersion of the physical quality index comprises: calculating the defect index of the cigarette products in the batch according to the deviation and the dispersion of the physical quality index; and calculating the physical quality index QI as:

wherein, Z is the deviation of the physical quality index, ρ is the dispersion of the physical quality index, f (Z, ρ) is a fitting curve function calculated according to the deviation Z and the dispersion ρ of the physical quality index, and the first threshold and the second threshold are respectively preset thresholds.

In some embodiments, the defect index is 30Z²+20Z+100ρ。

In some embodiments, the step of calculating the appearance quality index by a method of scoring the appearance quality of the batch of tobacco rod samples comprises: calculating the deduction score of each quality defect according to the product of each quality defect number and the corresponding unit deduction value in the appearance quality defect items of the cigarette samples in the batch; calculating the sum of the deduction scores of all kinds of quality defects to obtain the total deduction score of the appearance quality defects; and calculating a difference value obtained by subtracting the total deduction score of the appearance quality defects from the full score value to obtain an appearance quality index, wherein the appearance quality index is marked as a zero score when the difference value is a negative number.

In some embodiments, the step of calculating the cigarette rod rolling quality index includes: and weighting and summing the physical quality index and the appearance quality index to calculate the cigarette rolling quality index.

According to another aspect of the disclosed embodiments, there is provided a system for evaluating a cigarette rod rolling quality index, including: the index data calculation unit is used for calculating the deviation and the dispersion of the physical quality index based on the inspection data of each physical index of the cigarette samples in the batch; the physical quality index calculation unit is used for calculating to obtain a physical quality index according to the deviation and the dispersion of the physical quality index; the appearance quality index calculation unit is used for calculating the appearance quality index by a method of grading the appearance quality of the cigarette samples in the batch; and the rolling quality index calculation unit is used for calculating to obtain the cigarette rolling quality index according to the physical quality index and the appearance quality index.

In some embodiments, the inspection data of each physical index comprises inspection data of each physical index of self-inspection and inspection data of each physical index of special inspection; the index data calculation unit includes: the self-checking data calculation module is used for calculating the deviation and the dispersion of the physical self-checking quality indexes of the cigarette products in the batch based on the checking data of each physical index of the self-checking of the cigarette samples in the batch; the special inspection data calculation module is used for calculating the deviation and dispersion of the physical special inspection quality indexes of the cigarette products in the batch based on the inspection data of each physical index of the special inspection of the cigarette samples in the batch; the deviation calculation module is used for calculating the deviation of the physical quality index according to the deviation of the physical self-checking quality index and the deviation of the physical special-checking quality index; and the dispersion calculation module is used for calculating the dispersion of the physical quality index according to the dispersion of the physical self-checking quality index and the dispersion of the physical special-checking quality index.

In some embodiments, the self-test data calculation module is to: calculating the deviation and dispersion of the single self-checking physical indexes of the cigarette products in the batch based on the checking data of the physical indexes of the self-checking of the cigarette samples in the batch; weighting and summing the deviation degrees of the single self-checking physical indexes to calculate the deviation degree of the physical self-checking quality indexes of the cigarette products in the batch; and calculating the dispersion of the physical self-checking quality index of the cigarette products in the batch based on the dispersion of the single self-checking physical index, wherein the dispersion of the physical self-checking quality index is obtained by weighted summation of the dispersion of the single self-checking physical index, or the square of the dispersion of the single self-checking physical index is calculated, each is weighted summation is carried out on the square of the dispersion of the single self-checking physical index, and then the value after weighted summation is squared to calculate the dispersion of the physical self-checking quality index.

In some embodiments, the spot check data calculation module is to: calculating the deviation and dispersion of the single special physical indexes of the cigarette products in the batch based on the inspection data of the special physical indexes of the cigarette samples in the batch; weighting and summing the deviation degrees of the single-item special inspection physical indexes to calculate and obtain the deviation degree of the physical special inspection quality indexes of the cigarette products in the batch; and calculating to obtain the dispersion of the physical special inspection quality index of the cigarette products of the batch based on the dispersion of the single special inspection physical index, wherein the dispersion of the physical special inspection quality index is obtained by weighted summation of the dispersion of the single special inspection physical index, or the dispersion of the physical special inspection quality index is obtained by calculating each square of the dispersion of the single special inspection physical index, each square of the dispersion of the single special inspection physical index is weighted summation, and then the value after weighted summation is squared to calculate the dispersion of the physical special inspection quality index.

In some embodiments, the deviation degree calculation module is configured to perform weighted summation on the deviation degree of the physical self-test quality indicator and the deviation degree of the physical special-test quality indicator to calculate the deviation degree of the physical quality indicator.

In some embodiments, the dispersion calculation module is configured to perform weighted summation on the dispersion of the physical self-test quality indicator and the dispersion of the physical special test quality indicator to calculate the dispersion of the physical quality indicator; or calculating the square of the dispersion of the physical self-inspection quality index and the square of the dispersion of the physical special inspection quality index, carrying out weighted summation on the square of the dispersion of the physical self-inspection quality index and the square of the dispersion of the physical special inspection quality index, and then squaring the value after weighted summation to calculate the dispersion of the physical quality index.

In some embodiments, the physical quality index calculation unit is configured to calculate the defect index of the cigarette products in the batch according to the deviation and dispersion of the physical quality index, and calculate the physical quality index QI as:

In some embodiments, the defect index is 30Z²+20Z+100ρ。

In some embodiments, the appearance quality index calculation unit is configured to calculate deduction scores of various types of quality defects according to a product of the number of various types of quality defects in the appearance quality defect items of the cigarette samples in the batch and a corresponding unit deduction value, calculate a sum of deduction scores of various types of quality defects to obtain an appearance quality defect total deduction score, and calculate a difference value obtained by subtracting the appearance quality defect total deduction score from a full score to obtain an appearance quality index, where when the difference value is a negative number, the appearance quality index is recorded as a zero score.

In some embodiments, the cigarette rolling quality index calculation unit is configured to perform weighted summation on the physical quality index and the appearance quality index to calculate a cigarette rolling quality index.

According to another aspect of the disclosed embodiments, there is provided a system for evaluating a cigarette rod rolling quality index, including: a memory; and a processor coupled to the memory, the processor configured to perform the method as previously described based on instructions stored in the memory.

According to another aspect of embodiments of the present disclosure, there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the steps of the method as previously described.

In the method, the deviation and the dispersion of the physical quality index are calculated based on the inspection data of each physical index of the cigarette samples in the batch; calculating according to the deviation and dispersion of the physical quality index to obtain a physical quality index; calculating an appearance quality index by a method of scoring the appearance quality of the cigarette samples in the batch; and calculating according to the physical quality index and the appearance quality index to obtain the cigarette rolling quality index. The method realizes the evaluation of the cigarette rolling quality index.

Other features of the present disclosure and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description, serve to explain the principles of the disclosure.

The present disclosure may be more clearly understood from the following detailed description, taken with reference to the accompanying drawings, in which:

FIG. 1 is a flow chart illustrating a method for evaluating a cigarette rod rolling quality index according to some embodiments of the present disclosure;

FIG. 2 is a flow chart illustrating a method for evaluating a rod-to-rod quality index according to further embodiments of the present disclosure;

FIG. 3 is a flow chart illustrating a method of calculating the deviation and dispersion of a quality indicator of a physical self-test according to some embodiments of the present disclosure;

FIG. 4 is a flow chart illustrating a method of calculating a deviation and dispersion of a physical expertise quality index, according to some embodiments of the present disclosure;

FIG. 5 is a comparative schematic diagram schematically illustrating a measurement curve and a characteristic curve;

FIG. 6 is a schematic diagram illustrating a daily quality assessment trend for certain batches of tobacco products;

FIG. 7 is a schematic diagram schematically illustrating a monthly quality assessment trend for tobacco products within certain batches;

FIG. 8 is a schematic diagram illustrating the trend of quality evaluation of each machine for cigarette products in a batch;

FIG. 9 is a block diagram schematically illustrating a system for evaluating a rod-to-rod quality index according to some embodiments of the present disclosure;

FIG. 10 is a block diagram schematically illustrating a system for evaluating a rod-to-rod quality index according to further embodiments of the present disclosure;

figure 11 is a block diagram that schematically illustrates a system for evaluating a rod-by-rod quality index, in accordance with further embodiments of the present disclosure.

Detailed Description

Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.

Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.

The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses.

Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.

In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.

In the embodiment of the disclosure, quality index evaluation at each level takes a rolled production batch as a measurement object and takes physical and appearance index detection results of the batch as a quality index evaluation basis, so that the rolling production batch is defined by the disclosure. For example, the rolling production batch (hereinafter referred to as batch) is the cigarette products of the same brand and the same specification produced by the same date, class, serial number and equipment, and the specific included information is shown in table 1 below.

TABLE 1 composition of batch information for rolling production

Production workshop	For example: two-stage rolling and packing workshop
		Type of device	For example: rolling machine table
Device numbering	For example: 51 machine
		Class of computer	For example: first class
Date	For example: 2016-11-11
		Serial number	For example: 01,02

It should be noted that the above definition of roll production lot is only exemplary. It will be understood by those skilled in the art that roll production batches may be defined according to different needs. For example, the rolling production batch can be cigarette products of the same brand and the same specification produced by the same date and equipment. Accordingly, the definition of a batch in this disclosure is not so limited.

The following are definitions of the means, standard deviations, dispersion, and the like that may be used with embodiments of the present disclosure.

Mean value μ:

wherein x is_iN is the number of samples.

Standard deviation σ:

wherein x is_iN is the number of samples.

Deviation degree Z:

wherein mu is the actual mean value, the target value is the technical standard value, and sigma is_specIn order to set the standard deviation to a value,

here, the upper limit value indicates an index upper limit, and the lower limit value indicates an index lower limit. The sum of the upper limit value and the lower limit value can be determined in the process of designing the technical standard of the product index parameterThe lower limit value. The degree of deviation Z characterizes the degree of deviation, i.e. the accuracy, of the actual mean value from the technical standard value. The smaller the Z value is, the closer the representation actual mean value is to the technical standard value, namely the control accuracy is better.

Dispersion ρ:

wherein σ_measwedIs the actual standard deviation. The dispersion p is indicative of the degree of conformity, i.e., the accuracy, of the fluctuation condition (i.e., the actual standard deviation) of the actual control with the technical standard tolerance (i.e., the set standard deviation). The smaller the rho value is, the more the fluctuation condition representing the actual control can meet the technical standard tolerance, namely the better the control precision is.

Figure 1 is a flow chart illustrating a method for evaluating a cigarette roll quality index according to some embodiments of the present disclosure. As shown in fig. 1, the method includes steps S102 to S108.

In step S102, the deviation and dispersion of the physical quality index are calculated based on the inspection data of each physical index of the cigarette samples in the batch.

In some embodiments, the inspection data for each physical index may include inspection data for each physical index for self-inspection and inspection data for each physical index for special inspection.

For example, in the process of acquiring inspection data of physical self-inspection, the inspection data of each physical index of cigarette samples in a batch can be detected through equipment such as a production field comprehensive test bench, and then the inspection data of the self-inspection is transmitted to a system for evaluating the quality index of cigarette rolling.

For example, in the process of acquiring the inspection data of physical special inspection, the inspection data of each physical index of the cigarette samples in a batch can be detected through equipment such as an inspection room comprehensive test bench, and then the inspection data of the special inspection is transmitted to a system for evaluating the cigarette rolling quality index.

In some embodiments, this step S102 may include: and calculating the deviation and the dispersion of the physical self-checking quality indexes of the cigarette products in the batch based on the checking data of each physical index of the self-checking of the cigarette samples in the batch. For example, after the inspection data of each physical index of the self-inspection of the cigarette samples in the batch are collected, the deviation and the dispersion of the physical self-inspection quality index of the cigarette samples are calculated by analyzing the inspection data of the self-inspection, and the deviation and the dispersion of the samples are used as the deviation and the dispersion of the physical self-inspection quality index of the whole batch of products.

In some embodiments, the step S102 may further include: and calculating the deviation and the dispersion of the physical special inspection quality indexes of the cigarette products in the batch based on the inspection data of each physical index of the special inspection of the cigarette samples in the batch. For example, after the test data of each physical index of the specific test of the cigarette samples in the batch are collected, the deviation and the dispersion of the physical specific test quality indexes of the cigarette samples are calculated by analyzing the test data of the specific test, and the deviation and the dispersion of the samples are used as the deviation and the dispersion of the physical specific test quality indexes of the whole batch of products.

In some embodiments, the step S102 may further include: and calculating the deviation of the physical quality index according to the deviation of the physical self-checking quality index and the deviation of the physical special-checking quality index, and calculating the dispersion of the physical quality index according to the dispersion of the physical self-checking quality index and the dispersion of the physical special-checking quality index.

In some embodiments, the deviation of the physical self-test quality indicator and the deviation of the physical special-test quality indicator may be weighted and summed to calculate the deviation of the physical quality indicator.

That is, the degree of deviation Z of the physical quality index is:

Z＝Z_self-test×W′_Self-test+Z_{Special inspection}×W′_{Special inspection}， (5)

Wherein Z is_Self-testIs the deviation degree of a physical self-checking quality index, W'_Self-testIs a weight value, Z, corresponding to the degree of deviation of the physical self-test quality index_{Special inspection}Is the deviation degree of physical exclusive quality index, W'_{Special inspection}Is prepared by reacting withAnd the weight value corresponding to the deviation degree of the physical special quality index. Here, W'_Self-testAnd W'_{Special inspection}Can be determined according to actual conditions or actual requirements.

In some embodiments, the dispersion of the physical self-test quality indicator and the dispersion of the physical special-test quality indicator may be weighted and summed to calculate the dispersion of the physical quality indicator.

That is, the dispersion ρ of the physical quality index is:

ρ＝ρ_self-test×W"_Self-test+ρ_{Special inspection}×W"_{Special inspection}， (6)

Where ρ is_Self-testIs the dispersion of the quality index of physical self-inspection, W "_Self-testIs a weighted value, rho, corresponding to the dispersion of the physical self-test quality indicator_{Special inspection}For physical examination of the dispersion of the quality index, W "_{Special inspection}Is a weighted value corresponding to the dispersion of the physical quality index. Here, W "_Self-testAnd W'_{Special inspection}Can be determined according to actual conditions or actual requirements.

In other embodiments, the square of the dispersion of the physical self-test quality indicator and the square of the dispersion of the physical inspection quality indicator may be calculated, the square of the dispersion of the physical self-test quality indicator and the square of the dispersion of the physical inspection quality indicator may be weighted and summed, and then the weighted and summed value may be squared to calculate the dispersion of the physical quality indicator. That is to say that the first and second electrodes,

in step S104, a physical quality index is calculated from the deviation and dispersion of the physical quality index.

In some embodiments, this step S104 may include: and calculating the defect index of the cigarette products in the batch according to the deviation and the dispersion of the physical quality index. The step S104 may further include: calculating the physical quality index QI as follows:

wherein Z is the deviation of the physical quality index, rho is the dispersion of the physical quality index, and f (Z, rho) is a fitting curve function calculated according to the deviation Z and the dispersion rho of the physical quality index. The first threshold and the second threshold are respectively preset thresholds. For example, the first threshold is 3, the second threshold is 470, and so on.

For example, the defect index is 30Z²+20Z+100ρ。 (9)

The origin of the defect index is described in detail below in conjunction with fig. 5. Fig. 5 is a comparative diagram schematically showing a measurement curve and a characteristic curve. Fig. 5 shows a characteristic curve 51 and a measurement curve 52. Here, the characteristic curve 51 is a standard normal distribution curve, and the measurement curve 52 is a distribution curve of actual measurement data. Studies have shown that 86.64% of the measurements need to fall within + -1.5 sigma of the set target_specWithin the range.

Suppose that: ρ ═ aZ²+ bZ + c. From condition 1: z is 0, ρ is 1, and c is 1. From condition 2: z is 1.5, ρ is 0.025, and 2.25a +1.5b + c is 0.025. Here, the condition 1 and the condition 2 can be obtained by the following description.

The two conditions are combined to obtain: 9a +6b +3.9 ═ 0 (10)

Condition 3: 86.64% of all points on the curve have measurements falling within + -1.5 sigma of the set target_specWithin the range.

Let sigma_spec1, Z ═ μ -T |, ρ ═ σ_measwedWherein T is a target value.

When mu is greater than or equal to T, Z is equal to mu-T, since the measured sample population is subject to mean mu and variance

Is normally distributed. Thus, after a shift from the target value T, the mean value is μ -T and the variance is

Is normally distributed.I.e. after being converted into rho-Z, the obedience mean value is Z and the variance is rho²The distribution density function is:

according to the condition 3, the value is within. + -. 1.5. sigma_specThe cumulative distribution probability in the range is 0.8664, i.e.

Therefore, the method comprises the following steps:

after taking the value of Z from 0 to 1.5 with an interval of 0.25 as input, solving the corresponding rho value by adopting a function approximation method, wherein the result is as follows:

z is 0, ρ is 1 (i.e., condition 1);

Z＝0.25，ρ＝0.968；

Z＝0.5，ρ＝0.863；

Z＝0.75，ρ＝0.675；

Z＝1，ρ＝0.451；

Z＝1.25，ρ＝0.225；

z is 1.5 and ρ is 0.025 (i.e., condition 2).

Therefore, from the above results, when Z is 0.75, ρ is 0.675.

Therefore, there are:

combining equations (10) and (14) yields:

therefore, ρ ═ 0.3Z²-0.2Z+1。 (15)

In the same way, when mu<When T is reached, Z is T-mu, after deviation from the target value T, the mean value is T-mu, and the variance is

Is normally distributed. The following are also available:

ρ＝-0.3Z²-0.2Z+1。

the curve of the above relation (15) may be referred to as an ISO quality curve. If all the measurements falling on the curve are defined as 100 points, the defect index QI can be obtained_{Defect of}Is composed of

QI_{Defect of}＝30Z²+20Z+100ρ， (16)

The larger the defect index, the worse the quality control; the smaller the defect index, the better the quality control. And when the defect index exceeds a second threshold value, the central value and fluctuation of the steady-state process of the production of the batch do not meet the process requirements, the whole deviation is deviated from the control requirements, and the process control is invalid, so that the score of the physical quality index QI is 0. But the second threshold may be gradually reduced as the quality control improves.

In some embodiments, the quality condition may be characterized by ρ, Z, i.e., the compliance of the production performance condition with the technical standard is jointly characterized by ρ, Z.

In some embodiments, the exploration may be performed in conjunction with CPK (Process capability index) area determination.

(i) And (4) preliminarily drawing up scoring areas with different dispersion degrees (rho) by combining the judging area of the CP in the CPK. According to step iv, the results of the adjustments are shown in Table 2:

TABLE 2 scoring regions of different dispersion

CP	ρ	QI (preliminary drawing up)
			1.67 or more	0.5988	More than 95
1.33 or more	0.7519	Over 90
			0.833 or more	1.2005	Over 85
Less than 0.833	Less than 1.2004	More than 60

(ii) And preliminarily drawing up deduction subareas with different deviation degrees according to the deviation degree (Z) and a principle of deviating 3 times of gradient. According to step iv, the results of the adjustments are shown in Table 3:

TABLE 3 deduction of regions of different degrees of departure

K	Z	QI (deduction)
			1.3330	3.9990	0.0000
1.0000	3.0000	More than 50
			0.6670	2.0010	More than 35
0.3330	0.9990	More than 10
			0.1110	0.3330	1 or more
0.0370	0.1110	0.5 or more
			0.0127	0.0381	0.25 or more
0.0042	0.0126	0.05 or more
			0.0014	0.0042	0.01 or more

(iii) Increasing the maximum range of constraint and the zero point constraint, and according to the step iv, adjusting the result as shown in formula (17):

as can be seen in formula (17):

when Z is 0 and ρ is 0, 30Z²The +20Z +100 ρ is 0, and the score is 100 because the central value representing the production process of the batch does not deviate from the tolerance range as a whole and the process control is effective. When the Z value is greater than or equal to 3, the central value representing the production process of the batch deviates from the tolerance range as a whole, and the process control is failed, so that the score is 0. When Z and ρ are simultaneously increased to a certain degree (e.g., 30Z)²+20Z +100 rho is more than or equal to 470), the central value and fluctuation representing the steady-state process of the batch production do not meet the process requirements, the whole deviates from the control requirements, and the process control fails, so the score is 0. It should be noted that the second threshold value of 470 is merely exemplary, and the second threshold value may be changed according to the improvement of production or the production requirement. For example, the second threshold is 300, etc.

(iv) Solving a nonlinear equation system under a multi-constraint condition. And performing regression analysis according to a binary cubic equation according to a constraint condition formed by the three. The present disclosure contemplates a computational model QI ═ f (Z, ρ) formed after solving a system of nonlinear equations under multiple constraints using a two-dimensional cubic equation. For example, half-year data is used as the QI calculation result, and each department technician forms an expert group to judge, and if the fitting result does not exceed 4/5, the process returns to the step i. For example, using half-year data as fitting data, f (Z, ρ) is fitted as follows:

f(Z,ρ)＝99.007+2.71Z-20Z²+4.622Z³+7.1904ρ-23.4183ρ²+4.9268ρ³。

thus, there are

Returning to fig. 1, in step S106, the appearance quality index is calculated by scoring the appearance quality of the cigarette samples in the batch.

In some embodiments, this step S106 may include: and calculating the deduction score of each quality defect according to the product of each quality defect number and the corresponding unit deduction score in the appearance quality defect item of the cigarette samples in the batch.

For example, table 4 shows appearance quality defect entries and deduction rules for some embodiments.

TABLE 4 appearance quality Defect terms and deduction rules

For example, it is found through examination that there are 2 cigarettes with "loose head" problem and 4 cigarettes with "yellow spot" problem in the samples in a certain batch. The mark for the "empty head" defect is 2.0 × 2 to 4, and the mark for the "macular" defect is 0.5 × 4 to 2.

In some embodiments, the step S106 may further include: and calculating the sum of the deduction scores of all kinds of quality defects to obtain the total deduction score of the appearance quality defects.

For example, in the above example, the total number of appearance quality defects is 4 points +2 points 6 points.

In some embodiments, the step S106 may further include: and calculating the difference value of the full score value minus the total deduction score of the appearance quality defects to obtain the appearance quality index, wherein when the difference value is negative, the appearance quality index is marked as zero score (namely, when the score is negative, the appearance quality index is counted as zero score).

For example, if the full score is 100 points, the appearance quality index is 100 points to 6 points to 94 points in the above example. In this way, the appearance quality index is calculated by a method of scoring the appearance quality of cigarette samples in a batch.

In step S108, the cigarette rolling quality index is calculated according to the physical quality index and the appearance quality index.

In some embodiments, this step S108 may include: and weighting and summing the physical quality index and the appearance quality index to calculate the cigarette rolling quality index.

For example, the physical quality index is assigned a weight value of a%, and the appearance quality index is assigned a weight value of B%, where a% + B% is 1. Then

The cigarette rolling quality index is equal to the physical quality index multiplied by A% + the appearance quality index multiplied by B%.

To this end, a method for evaluating a cigarette rod rolling quality index according to some embodiments of the present disclosure is provided. In the method, the deviation and the dispersion of physical quality indexes are calculated based on the inspection data of each physical index of cigarette samples in a batch; calculating according to the deviation and dispersion of the physical quality index to obtain a physical quality index; calculating an appearance quality index by a method of scoring the appearance quality of the cigarette samples in the batch; and calculating according to the physical quality index and the appearance quality index to obtain the cigarette rolling quality index. The method realizes the evaluation of the cigarette rolling quality index.

In the method, the deviation and the dispersion are included in the method for evaluating the cigarette rolling quality index, the degree of deviation of the actual detection data of the index from the set value of the index is considered, and the overall fluctuation condition of the actual detection data of the index is also considered, so that the scientific evaluation and analysis capability based on mathematical statistics data and the quality management decision capability based on fact data are improved. The method is beneficial to finding the quality short plate, provides data basis and verification basis for quality improvement and defect solving, and also provides basic data for batch product quality tracing.

For example, table 5 shows an exemplary list of physical quality indices and appearance quality indices. Table 6 shows an exemplary list of roll quality indices.

TABLE 5 physical and appearance quality index List

TABLE 6 Rolling quality index List

Figure 2 is a flow chart illustrating a method for evaluating a rod-to-rod quality index according to other embodiments of the present disclosure. As shown in fig. 2, the method includes steps S202 to S212.

In step S202, the deviation and dispersion of the physical self-checking quality index of the cigarette products in the batch are calculated based on the checking data of each physical index of the self-checking of the cigarette samples in the batch. The method for calculating the deviation and dispersion of the quality index of the physical self-test will be described in detail later with reference to fig. 3.

In some embodiments, the quality index of the physical self-test can be calculated according to the deviation and dispersion of the quality index of the physical self-test. The physical self-test quality index may be calculated, for example, by the same or similar formula as formula (8) (or formula (18)). For example, the deviation and dispersion of the quality index of the physical self-test can be substituted into the formula (8) (or the formula (18)) to obtain the quality index of the physical self-test.

In step S204, the deviation and dispersion of the physical quality index of the cigarettes in the batch are calculated based on the inspection data of each physical index of the cigarettes in the batch. The method for calculating the deviation and dispersion of the physical quality index will be described in detail later with reference to fig. 4.

In some embodiments, the physical specific quality index may be calculated from the deviation and dispersion of the physical specific quality index. The physical quality index can be calculated, for example, by the same or similar formula as formula (8) (or formula (18)). For example, the physical examination quality index can be obtained by substituting the deviation and dispersion of the physical examination quality index into the formula (8) (or the formula (18)). For example, table 7 shows an exemplary physical quality index list for the specific examination.

TABLE 7 physical examination quality index List

In step S206, the deviation of the physical quality index is calculated according to the deviation of the physical self-inspection quality index and the deviation of the physical special inspection quality index, and the dispersion of the physical quality index is calculated according to the dispersion of the physical self-inspection quality index and the dispersion of the physical special inspection quality index.

In step S208, the physical quality index is calculated according to the deviation and dispersion of the physical quality index.

In step S210, an appearance quality index is calculated by a method of scoring the appearance quality of the cigarette samples in the batch.

In step S212, the physical quality index and the appearance quality index are weighted and summed to calculate a cigarette rolling quality index.

To this end, methods for evaluating a rod-to-rod quality index according to further embodiments of the present disclosure are provided. The method improves the scientific evaluation analysis capability based on mathematical statistics data and the quality management decision capability based on factual data. The method is beneficial to finding the quality short plate, provides data basis and verification basis for quality improvement and defect solving, and also provides basic data for batch product quality tracing. In addition, the method can also find the deviation and dispersion condition of each level of indexes, and is beneficial to quality analysis.

Figure 3 is a flow chart illustrating a method of calculating the deviation and dispersion of a quality indicator of a physical self-test according to some embodiments of the present disclosure. The method includes steps S302-S306.

In step S302, based on the inspection data of each physical index of the self-inspection of the cigarette samples in the batch, the deviation and dispersion of the individual self-inspection physical indexes of the cigarette products in the batch are calculated.

Table 8 shows an exemplary single item physical metric definition.

TABLE 8 Single physical index Definitions

Key single physical index
	Circumference of circle
Singleweight
	Suction resistance
……

Here, the smoking resistance refers to the smoking resistance of smoking cigarettes of a consumer or a smoker being simulated and measured by using special detection equipment.

In some embodiments, the deviation and the dispersion of each individual self-test physical index can be calculated through formulas (1) to (4) based on the test data of each physical index of the self-test of the cigarette samples in the batch. In the process, the mean value, the standard deviation and the like of each single physical index can be calculated. For example, table 9 shows the mean, standard deviation of exemplary individual physical indicators.

TABLE 9 mean and standard deviation of single physical index

In some embodiments, the physical quality index of each individual self-check can be calculated according to the deviation and dispersion of the physical index of each individual self-check. The single term self-test physical quality index may be calculated, for example, by the same or similar formula as formula (8) (or formula (18)). For example, the deviation and dispersion of a single-term self-checking physical index can be substituted into the formula (8) (or the formula (18)) to obtain the single-term self-checking physical quality index of the single term. For example, table 10 shows some exemplary single-term self-test physical quality indices.

TABLE 10 some list of single item self-test physical quality indices

In step S304, the deviation of the physical self-checking index of the single item is weighted and summed to calculate the deviation of the physical self-checking quality index of the cigarette product of the batch. That is, the deviation of each individual self-checking physical index is multiplied by the corresponding weight, and then the sum is calculated by adding the weights, so that the deviation of the physical self-checking quality index can be obtained.

Deviation Z of physical self-checking quality index_Self-testComprises the following steps:

wherein the content of the first and second substances,

is the c_iThe deviation degree of the single self-checking physical index,

is as follows_iAnd the weight value corresponding to the deviation of the single self-checking physical index.

In step S306, the dispersion of the physical self-checking quality index of the cigarette product in the batch is calculated based on the dispersion of the single self-checking physical index.

In some embodiments, the dispersion of the quality indicator of the physical self-test can be calculated by weighted summation of the dispersion of the single self-test physical indicator. That is, the dispersion of each single self-checking physical index is multiplied by the corresponding weight, and then they are added to calculate the sum, so as to obtain the deviation of the physical self-checking quality indexDivergence. I.e. the dispersion ρ of the quality index of the physical self-test_Self-testComprises the following steps:

wherein the content of the first and second substances,

is the c_iThe dispersion of the single self-checking physical index,

is as follows_iAnd (4) the weight value corresponding to the dispersion of the single self-checking physical index.

In other embodiments, the square of the dispersion of each single self-checking physical index can be calculated, the squares of the dispersion of each single self-checking physical index are weighted and summed, and then the weighted and summed value is squared to calculate the dispersion of the physical self-checking quality index. I.e. the dispersion ρ of the quality index of the physical self-test_Self-testComprises the following steps:

therefore, a method for calculating the deviation and the dispersion of the physical self-inspection quality index is provided. By the method, the deviation and the dispersion of the physical self-inspection quality index can be obtained.

Fig. 4 is a flow chart illustrating a method of calculating a deviation and dispersion of a physical expertise quality index according to some embodiments of the present disclosure. As shown in fig. 4, the method includes steps S402 to S406.

In step S402, based on the inspection data of each physical index for the specific inspection of the cigarette samples in the batch, the deviation and dispersion of the physical index for the single specific inspection of the cigarette products in the batch are calculated.

For example, the physical indicators of a single item of a cigarette product may include: circumference, basis weight, suction resistance, hardness, and the like.

In some embodiments, the deviation and dispersion of each individual physical index of the cigarettes in the batch can be calculated through formulas (1) to (4) based on the inspection data of each physical index of the cigarettes in the batch. In the process, the mean value, the standard deviation and the like of each single physical index can be calculated.

In some embodiments, the physical quality index of each individual special inspection can be calculated according to the deviation and dispersion of each individual special inspection physical index. Each individual item specific physical quality index may be calculated, for example, by the same or similar formula as formula (8) (or formula (18)). For example, the deviation and dispersion of a single-term specific physical index can be substituted into the formula (8) (or the formula (18)) to obtain the single-term specific physical quality index of the single term.

In step S404, the deviation degrees of the physical specific examination quality indexes of the single specific examination physical indexes are weighted and summed to calculate the deviation degree of the physical specific examination quality indexes of the cigarette products of the batch. That is, the deviation of each individual examination physical index is multiplied by the corresponding weight, and then the deviation is added to calculate the sum, so that the deviation of the physical examination quality index can be obtained.

Deviation Z of physical quality index_{Special inspection}Comprises the following steps:

wherein the content of the first and second substances,

is d at_iThe deviation degree of the physical index of the single item special inspection,

is as follows_iAnd the weight value corresponding to the deviation degree of the single special physical index.

In step S406, the dispersion of the physical specific inspection quality indexes of the cigarette products in the batch is calculated based on the dispersion of the single specific inspection physical indexes.

In some embodiments, the dispersion of the physical spot quality indicator may be calculated by weighted summation of the dispersions of the individual spot physical indicators. That is, the dispersion of each individual examination physical index is multiplied by the corresponding weight, and then they are added to calculate the sum, so as to obtain the dispersion of the physical examination quality index. That is, the dispersion ρ of the physical examination quality index_{Special inspection}Comprises the following steps:

wherein the content of the first and second substances,

is d at_iThe dispersion of the physical indexes of the single item special examination,

is as follows_iAnd the weight value corresponding to the dispersion of the physical index of the single item special inspection.

In other embodiments, the square of the dispersion of each individual examination physical index can be calculated, the squares of the dispersion of each individual examination physical index can be weighted and summed, and then the weighted and summed value can be squared to calculate the dispersion of the physical examination quality index. That is, the dispersion ρ of the physical examination quality index_{Special inspection}Comprises the following steps:

thus, a method of calculating the deviation and dispersion of a physical quality index for a specific examination is provided. By the method, the deviation and the dispersion of the physical quality index can be obtained.

In the embodiment of the disclosure, the quality states of all levels of a company are comprehensively reflected through statistics and multidimensional analysis of evaluation data, and quality management and decision based on fact data are facilitated to be formed. For example, fig. 6 shows the daily quality evaluation trend of cigarette products in a certain batch, fig. 7 shows the monthly quality evaluation trend of cigarette products in a certain batch, and fig. 8 shows the quality evaluation trends of each machine of cigarette products in a certain batch. Through these analysis maps, statistical and multidimensional analysis of the evaluation data can be achieved.

In addition, the multidimensional analysis can also comprise quality evaluation trends of key physical indexes of the volume packets, quality comparison analysis of each brand of the volume packets, quality comparison analysis of each team and group of the volume packets, quality comparison analysis of each model of the volume packets, quality comparison analysis of each machine of the volume packets and the like. Through multi-dimensional analysis, a mass short plate is found, which can promote quality improvement.

In some embodiments, the roll quality index evaluation method can be solidified into an informatization system, so that the quality index conditions of all levels can be analyzed globally or in a refining manner, quality management, assessment and analysis are facilitated, quality problems are found, analyzed and solved from data, and product quality is improved.

Figure 9 is a block diagram that schematically illustrates a system for evaluating a rod-by-rod quality index, according to some embodiments of the present disclosure. As shown in fig. 9, the system includes an index data calculation unit 920, a physical quality index calculation unit 940, an appearance quality index calculation unit 960, and a roll quality index calculation unit 980.

The index data calculation unit 920 may be configured to calculate a deviation and a dispersion of the physical quality index based on the inspection data of each physical index of the cigarette samples in the batch.

The physical quality index calculation unit 940 may be configured to calculate the physical quality index according to the deviation and the dispersion of the physical quality index.

The appearance quality index calculation unit 960 may be configured to calculate the appearance quality index by scoring the appearance quality of the cigarette samples within a batch.

The rolling quality index calculation unit 980 can be used for calculating the cigarette rolling quality index according to the physical quality index and the appearance quality index.

In the system of this embodiment, the index data calculation unit calculates the deviation and dispersion of the physical quality index based on the inspection data of each physical index of the cigarette samples in the batch. And the physical quality index calculating unit calculates the physical quality index according to the deviation and the dispersion of the physical quality index. And the appearance quality index calculating unit calculates the appearance quality index by a method of grading the appearance quality of the cigarette samples in the batch. And the rolling quality index calculating unit calculates to obtain the cigarette rolling quality index according to the physical quality index and the appearance quality index. The system realizes the evaluation of the cigarette rolling quality index.

In the system, the deviation and the dispersion are also brought into a system for evaluating the cigarette rolling quality index, the degree of deviation of the actual detection data of the indexes from the set value of the indexes is considered, and the overall fluctuation condition of the actual detection data of the indexes is also considered, so that the scientific evaluation and analysis capability based on mathematical statistics data and the quality management decision capability based on fact data are improved. The system is beneficial to finding the quality short plate, provides data basis and verification basis for quality improvement and defect solving, and also provides basic data for batch product quality tracing.

In some embodiments, as shown in fig. 9, the index data calculation unit includes a self-test data calculation module 922, a spot test data calculation module 924, a deviation calculation module 926, and a dispersion calculation module 928.

The self-checking data calculation module 922 may be configured to calculate, based on the inspection data of each physical indicator of the self-checking of the cigarette samples in a batch, a deviation and a dispersion of the physical self-checking quality indicators of the cigarette products in the batch.

The specific inspection data calculating module 924 may be configured to calculate, based on the inspection data of each physical indicator of the specific inspection of the cigarette samples in the batch, a deviation and a dispersion of the physical specific inspection quality indicators of the cigarette products in the batch.

The deviation calculation module 926 can be configured to calculate the deviation of the physical quality indicator according to the deviation of the physical self-test quality indicator and the deviation of the physical special test quality indicator.

The dispersion calculation module 928 may be configured to calculate the dispersion of the physical quality indicator according to the dispersion of the physical self-test quality indicator and the dispersion of the physical special test quality indicator.

In some embodiments, the self-test data calculation module 922 may be configured to: calculating the deviation and dispersion of the single self-checking physical indexes of the cigarette products in the batch based on the checking data of the physical indexes of the self-checking of the cigarette samples in the batch; weighting and summing the deviation degrees of the single self-checking physical indexes to calculate the deviation degree of the physical self-checking quality indexes of the cigarette products in the batch; and calculating the dispersion of the physical self-checking quality index of the cigarette products of the batch based on the dispersion of the single self-checking physical index.

For example, the self-test data calculation module 922 may calculate the dispersion of the quality indicator of the physical self-test by weighted summation of the dispersions of the individual self-test physical indicators.

For another example, the self-test data calculation module 922 may calculate the square of the dispersion of each single self-test physical indicator, perform weighted summation on the square of the dispersion of each single self-test physical indicator, and then square the weighted summation to calculate the dispersion of the physical self-test quality indicator.

In some embodiments, the spot data calculation module 924 may be configured to: calculating the deviation and dispersion of the single special physical indexes of the cigarette products in the batch based on the inspection data of the special physical indexes of the cigarette samples in the batch; weighting and summing the deviation degrees of the single special inspection physical indexes to calculate the deviation degree of the physical special inspection quality indexes of the cigarette products of the batch; and calculating the dispersion of the physical special inspection quality indexes of the cigarette products of the batch based on the dispersion of the single special inspection physical indexes.

For example, the spot data calculation module 924 may calculate the dispersion of the physical spot quality indicator by weighted summation of the dispersions of the individual spot physical indicators.

For another example, the special examination data calculating module 924 may calculate the square of the dispersion of each individual special examination physical index, perform weighted summation on the square of the dispersion of each individual special examination physical index, and then square the weighted summation value to calculate the dispersion of the physical special examination quality index.

In some embodiments, the deviation calculation module 926 may be configured to perform a weighted summation of the deviation of the physical self-test quality indicator and the deviation of the physical self-test quality indicator to calculate the deviation of the physical quality indicator.

In some embodiments, the dispersion calculation module 928 may be configured to perform a weighted summation of the dispersion of the physical self-test quality indicator and the dispersion of the physical self-test quality indicator to calculate the dispersion of the physical quality indicator.

In other embodiments, the dispersion calculation module 928 may be configured to calculate the square of the dispersion of the physical self-test quality indicator and the square of the dispersion of the physical inspection-specific quality indicator, perform weighted summation on the square of the dispersion of the physical self-test quality indicator and the square of the dispersion of the physical inspection-specific quality indicator, and then square the weighted summation to calculate the dispersion of the physical quality indicator.

In some embodiments, the physical quality index calculation unit 940 may be configured to calculate the defect index of the cigarette products in the batch according to the deviation and the dispersion of the physical quality index, and calculate the physical quality index QI as:

In some embodiments, the defect index is ═30Z²+20Z+100ρ。

In some embodiments, the appearance quality index calculation unit 960 may be configured to calculate a deduction score of each type of quality defect according to a product of the number of each type of quality defect and a corresponding unit deduction value in the appearance quality defect item of the cigarette sample in the batch, calculate a sum of the deduction scores of each type of quality defect to obtain an appearance quality defect total deduction score, and calculate a difference between the full score and the appearance quality defect total deduction score to obtain the appearance quality index. When the difference is negative, the appearance quality index is marked as zero.

In some embodiments, the roll quality index calculation unit 980 may be configured to perform a weighted summation of the physical quality index and the appearance quality index to calculate a cigarette roll quality index.

Figure 10 is a block diagram that schematically illustrates a system for evaluating a rod-by-rod quality index, in accordance with further embodiments of the present disclosure. The system includes a memory 1010 and a processor 1020. Wherein:

the memory 1010 may be a magnetic disk, flash memory, or any other non-volatile storage medium. The memory is used for storing instructions in at least one corresponding embodiment in fig. 1 to 4.

The processor 1020, coupled to the memory 1010, may be implemented as one or more integrated circuits, such as a microprocessor or microcontroller. The processor 1020 is used for executing instructions stored in the memory, evaluating the quality index by adopting methods such as deviation Z, dispersion rho and deduction, comprehensively representing the rolling quality level, and providing a basis for aspects such as cigarette quality management, assessment, quality improvement and statistical analysis.

In some embodiments, as also shown in FIG. 11, the system 1100 includes a memory 1110 and a processor 1120. Processor 1120 is coupled to memory 1110 by a BUS 1130. The system 1100 may also be coupled to an external storage device 1150 via a storage interface 1140 for retrieving external data, and may also be coupled to a network or another computer system (not shown) via a network interface 1160, which will not be described in detail herein.

In the embodiment, the data instruction is stored in the memory, the instruction is processed by the processor, the quality index is evaluated by adopting the methods of deviation Z, dispersion rho, deduction and the like, the rolling quality level is comprehensively represented, and a basis is provided for aspects of cigarette quality management, assessment, quality improvement, statistical analysis and the like.

In other embodiments, the present disclosure also provides a computer-readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the steps of the method in at least one of the corresponding embodiments of fig. 1-4. As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, apparatus, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

Thus far, the present disclosure has been described in detail. Some details that are well known in the art have not been described in order to avoid obscuring the concepts of the present disclosure. It will be fully apparent to those skilled in the art from the foregoing description how to practice the presently disclosed embodiments.

The method and system of the present disclosure may be implemented in a number of ways. For example, the methods and systems of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for the steps of the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above unless specifically stated otherwise. Further, in some embodiments, the present disclosure may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.

Although some specific embodiments of the present disclosure have been described in detail by way of example, it should be understood by those skilled in the art that the foregoing examples are for purposes of illustration only and are not intended to limit the scope of the present disclosure. It will be appreciated by those skilled in the art that modifications may be made to the above embodiments without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.

Claims

1. A method for evaluating a cigarette rod rolling quality index, comprising:

calculating the deviation and dispersion of the physical quality indexes based on the inspection data of each physical index of the cigarette samples in the batch;

calculating according to the deviation and dispersion of the physical quality index to obtain a physical quality index;

calculating an appearance quality index by a method of scoring the appearance quality of the cigarette samples in the batch; and

calculating according to the physical quality index and the appearance quality index to obtain a cigarette rolling quality index;

the inspection data of each physical index comprises inspection data of each physical index of self-inspection and inspection data of each physical index of special inspection;

the step of calculating the deviation and dispersion of the physical quality index comprises the following steps:

calculating the deviation and dispersion of the physical self-checking quality indexes of the cigarette products in the batch based on the checking data of each physical index of the self-checking of the cigarette samples in the batch;

calculating the deviation and dispersion of the physical special inspection quality indexes of the cigarette products of the batch based on the inspection data of each physical index of the special inspection of the cigarette samples in the batch; and

calculating the deviation of the physical quality index according to the deviation of the physical self-checking quality index and the deviation of the physical special-checking quality index, and calculating the dispersion of the physical quality index according to the dispersion of the physical self-checking quality index and the dispersion of the physical special-checking quality index.

2. The method of claim 1, wherein the step of calculating the deviation and dispersion of the quality indicator of the physical self-test comprises:

calculating the deviation and dispersion of the single self-checking physical indexes of the cigarette products in the batch based on the checking data of the physical indexes of the self-checking of the cigarette samples in the batch;

weighting and summing the deviation degrees of the single self-checking physical indexes to calculate the deviation degree of the physical self-checking quality indexes of the cigarette products in the batch; and

calculating the dispersion of the physical self-checking quality indexes of the cigarette products in the batch based on the dispersion of the single self-checking physical indexes,

wherein the dispersion of the physical self-checking quality index is calculated by weighted summation of the dispersion of the single self-checking physical index,

or calculating the square of the dispersion of each single self-checking physical index, performing weighted summation on the square of the dispersion of each single self-checking physical index, and squaring the value after weighted summation to calculate the dispersion of the physical self-checking quality index.

3. The method of claim 1, wherein the step of calculating the deviation and dispersion of the physical expertise quality index comprises:

calculating the deviation and dispersion of the single special physical indexes of the cigarette products in the batch based on the inspection data of the special physical indexes of the cigarette samples in the batch;

weighting and summing the deviation degrees of the single-item special inspection physical indexes to calculate and obtain the deviation degree of the physical special inspection quality indexes of the cigarette products in the batch; and

calculating the dispersion of the physical special inspection quality indexes of the cigarette products of the batch based on the dispersion of the single special inspection physical indexes,

wherein the dispersion of the physical examination quality index is calculated by weighted summation of the dispersions of the single examination physical indexes,

or calculating the square of the dispersion of each single-item special detection physical index, performing weighted summation on the square of the dispersion of each single-item special detection physical index, and squaring the value after weighted summation to calculate the dispersion of the physical special detection quality index.

4. The method of claim 1, wherein the step of calculating the deviation of the physical quality indicator from the deviation of the physical self-test quality indicator and the deviation of the physical special test quality indicator comprises:

and weighting and summing the deviation of the physical self-inspection quality index and the deviation of the physical special-inspection quality index to calculate the deviation of the physical quality index.

5. The method according to claim 1, wherein the step of calculating the dispersion of the physical quality indicator according to the dispersion of the physical self-test quality indicator and the dispersion of the physical special test quality indicator comprises:

carrying out weighted summation on the dispersion of the physical self-detection quality index and the dispersion of the physical special-detection quality index to calculate the dispersion of the physical quality index;

or calculating the square of the dispersion of the physical self-inspection quality index and the square of the dispersion of the physical special inspection quality index, carrying out weighted summation on the square of the dispersion of the physical self-inspection quality index and the square of the dispersion of the physical special inspection quality index, and then squaring the value after weighted summation to calculate the dispersion of the physical quality index.

6. The method of claim 1, wherein the step of calculating the physical quality index from the deviation and dispersion of the physical quality index comprises:

calculating the defect index of the cigarette products in the batch according to the deviation and the dispersion of the physical quality index; and

calculating the physical quality index QI as follows:

7. The method of claim 6, wherein,

the defect index is 30Z²+20Z+100ρ。

8. The method according to claim 1, wherein the step of calculating the appearance quality index by means of a method of scoring the appearance quality of the batch of tobacco rod samples comprises:

calculating the deduction score of each quality defect according to the product of each quality defect number and the corresponding unit deduction value in the appearance quality defect items of the cigarette samples in the batch;

calculating the sum of the deduction scores of all kinds of quality defects to obtain the total deduction score of the appearance quality defects; and

and calculating a difference value obtained by subtracting the total deduction score of the appearance quality defects from the full score value to obtain an appearance quality index, wherein the appearance quality index is marked as zero score when the difference value is a negative number.

9. The method of claim 1, wherein the step of calculating the cigarette rod rolling quality index comprises:

and weighting and summing the physical quality index and the appearance quality index to calculate the cigarette rolling quality index.

10. A system for evaluating a cigarette rod rolling quality index, comprising:

the index data calculation unit is used for calculating the deviation and the dispersion of the physical quality index based on the inspection data of each physical index of the cigarette samples in the batch;

the physical quality index calculation unit is used for calculating to obtain a physical quality index according to the deviation and the dispersion of the physical quality index;

the appearance quality index calculation unit is used for calculating the appearance quality index by a method of grading the appearance quality of the cigarette samples in the batch; and

and the rolling quality index calculating unit is used for calculating to obtain the cigarette rolling quality index according to the physical quality index and the appearance quality index.

11. The system of claim 10, wherein,

the index data calculation unit includes:

the self-checking data calculation module is used for calculating the deviation and the dispersion of the physical self-checking quality indexes of the cigarette products in the batch based on the checking data of each physical index of the self-checking of the cigarette samples in the batch;

the special inspection data calculation module is used for calculating the deviation and dispersion of the physical special inspection quality indexes of the cigarette products in the batch based on the inspection data of each physical index of the special inspection of the cigarette samples in the batch;

the deviation calculation module is used for calculating the deviation of the physical quality index according to the deviation of the physical self-checking quality index and the deviation of the physical special-checking quality index; and

and the dispersion calculation module is used for calculating the dispersion of the physical quality index according to the dispersion of the physical self-checking quality index and the dispersion of the physical special-checking quality index.

12. The system of claim 11, wherein,

the self-checking data calculation module is used for: calculating the deviation and dispersion of the single self-checking physical indexes of the cigarette products in the batch based on the checking data of the physical indexes of the self-checking of the cigarette samples in the batch; weighting and summing the deviation degrees of the single self-checking physical indexes to calculate the deviation degree of the physical self-checking quality indexes of the cigarette products in the batch; and calculating the dispersion of the physical self-checking quality indexes of the cigarette products of the batch based on the dispersion of the single self-checking physical indexes,

13. The system of claim 11, wherein,

the special inspection data calculation module is used for: calculating the deviation and dispersion of the single special physical indexes of the cigarette products in the batch based on the inspection data of the special physical indexes of the cigarette samples in the batch; weighting and summing the deviation degrees of the single-item special inspection physical indexes to calculate and obtain the deviation degree of the physical special inspection quality indexes of the cigarette products in the batch; and calculating the dispersion of the physical special inspection quality indexes of the cigarette products of the batch based on the dispersion of the single special inspection physical indexes,

14. The system of claim 11, wherein,

and the deviation degree calculation module is used for weighting and summing the deviation degree of the physical self-detection quality index and the deviation degree of the physical special-detection quality index to calculate the deviation degree of the physical quality index.

15. The system of claim 11, wherein,

the dispersion degree calculation module is used for carrying out weighted summation on the dispersion degree of the physical self-detection quality index and the dispersion degree of the physical special-detection quality index so as to calculate the dispersion degree of the physical quality index; or calculating the square of the dispersion of the physical self-inspection quality index and the square of the dispersion of the physical special inspection quality index, carrying out weighted summation on the square of the dispersion of the physical self-inspection quality index and the square of the dispersion of the physical special inspection quality index, and then squaring the value after weighted summation to calculate the dispersion of the physical quality index.

16. The system of claim 10, wherein,

the physical quality index computing unit is used for computing the defect index of the cigarette products in the batch according to the deviation and the dispersion of the physical quality index, and computing the physical quality index QI as follows:

17. The system of claim 16, wherein,

the defect index is 30Z²+20Z+100ρ。

18. The system of claim 10, wherein,

the appearance quality index calculating unit is used for calculating deduction scores of various quality defects according to the product of the number of various quality defects and corresponding unit deduction values in appearance quality defect items of cigarette samples in batches, calculating the sum of the deduction scores of various quality defects to obtain an appearance quality defect total deduction score, and calculating the difference value of subtracting the appearance quality defect total deduction score from a full score to obtain an appearance quality index, wherein the appearance quality index is recorded as a zero score when the difference value is a negative number.

19. The system of claim 10, wherein,

and the rolling quality index calculation unit is used for weighting and summing the physical quality index and the appearance quality index to calculate and obtain the cigarette rolling quality index.

20. A system for evaluating a cigarette rod rolling quality index, comprising:

a memory; and

a processor coupled to the memory, the processor configured to perform the method of any of claims 1-9 based on instructions stored in the memory.

21. A computer-readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the steps of the method of any one of claims 1 to 9.