A method for evaluating the quality of a cigarette roll

Abstract

The application provides a method for evaluating the rolling quality of cigarettes, comprising: sampling the same batch of cigarettes being produced multiple times, and obtaining sample data corresponding to each physical index of the cigarettes, wherein the physical index comprises single cigarette weight, draw resistance, circumference, hardness, length, total ventilation rate of the cigarette, and cigarette hardness; calculating the average value corresponding to each index according to the sample data of the physical index, and calculating the variance, standard deviation, and coefficient of variation of each index according to the average value and the design standard value, so as to determine whether each index is within the range specified by the standard; if yes, the stability of the rolling quality meets the design requirements, otherwise, the position effect variance analysis and the dispersion effect variance analysis are performed on the physical index of the cigarettes, so as to determine the influencing factors of the stability of the cigarette quality. The application can give an overall evaluation of the operation of the machine set, so as to quickly eliminate the risk, reduce the production cost, and improve the product quality.

Description

Technical Field

[0001] This invention relates to the technical field of cigarette production quality testing, and in particular to a method for evaluating the quality of cigarette packs. Background Technology

[0002] As one of the processes in cigarette production, cigarette rolling and packaging is responsible for rolling tobacco into cigarette sticks, packaging the cigarette sticks into small cigarette packs, then packaging the small cigarette packs into cartons of cigarettes, and finally packing the cigarette cartons into finished cigarettes. Currently, during the rolling and packaging process, product quality problems such as uncontrolled cartons, excessively light or heavy cartons, and empty rolls frequently occur. Machine shutdowns caused by quality issues are common. When quality problems occur, operators cannot quantitatively assess the severity of the problem, nor can they provide an overall evaluation of the machine's operation based on the occurrence of each quality issue. Therefore, managing the various quality risks in the cigarette rolling process to quickly eliminate risks, reduce production costs, and improve product quality is of great significance. Summary of the Invention

[0003] This invention provides a method for evaluating the quality of cigarette rolling and packaging, which solves the problems of slippage, excessive weight, and empty ends that easily occur in existing cigarette rolling and packaging units during the rolling process. These problems prevent operators from quantitatively judging the severity of the quality issues. This method can accurately provide an overall evaluation of the unit's operation, thereby quickly eliminating risks, reducing production costs, and improving product quality.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A method for evaluating the quality of cigarette packs, comprising:

[0006] Multiple samples were taken from the same batch of cigarettes in production, and sample data corresponding to various physical indicators of the cigarettes were obtained. The physical indicators include: single cigarette mass, draw resistance, circumference, hardness, length, total ventilation rate of the cigarette and hardness of the cigarette.

[0007] The average value of each physical index is calculated based on the sample data, and the variance, standard deviation and coefficient of variation of each index are calculated based on the average value and the design standard value to determine whether each index is within the range specified by the standard.

[0008] If so, the stability of the cigarette pack quality meets the design requirements; otherwise, position effect variance analysis and divergence effect variance analysis are performed on the physical indicators of the cigarette to determine the influencing factors of the cigarette quality stability.

[0009] Preferred options also include:

[0010] The overall average values ​​of the single cigarette weight, draw resistance, circumference, hardness and length of each batch of cigarettes are compared with the corresponding design standard values. The consistency of the quality of each batch of cigarette packs is evaluated by judging whether there is a statistically significant difference between the two.

[0011] If there is a statistically significant difference between the two, it indicates that the quality indicators of this batch of rolls and packages are inconsistent with the standard design values;

[0012] If there is no statistically significant difference between the two, it indicates that the quality indicators of this batch of rolls are consistent with the standard design values.

[0013] Preferably, the comparison of the overall average value of the single cigarette weight, draw resistance, circumference, hardness, and length of each batch with the corresponding design standard value includes:

[0014] The consistency of quality of a single batch of rolls and packages is evaluated by using the single population mean t-test to assess the consistency between the quality of a single batch of rolls and packages and the standard design value.

[0015] t-test statistic: in, s is the population mean, s is the population standard deviation, μ0 is the population mean to be tested, and n is the sample size.

[0016] Preferably, the comparison of the overall average value of the single cigarette weight, draw resistance, circumference, hardness, and length of each batch with the corresponding design standard value further includes:

[0017] To evaluate the consistency of quality between two batches of roll packaging, a two-sample t-test was used.

[0018] Two-sample t-test statistic: in, and Let d0 be the population mean corresponding to the two samples, d0 be the hypothetical difference between the two population means, n1 and n2 be the number of the first and second samples, and s1 and s2 be the standard deviations of the first and second samples.

[0019] Preferably, the comparison of the overall average value of the single cigarette weight, draw resistance, circumference, hardness, and length of each batch with the corresponding design standard value further includes:

[0020] To evaluate the consistency of quality across multiple batches of rolls and packages, multiple population mean tests were used. First, different production batches were considered as one factor, and the number of different production batches was regarded as the level number of the factor.

[0021] Sampling inspections were conducted on any three or more different production batches of cigarette products. One-way ANOVA was used to infer whether the factor "different production batches" had a statistically significant impact on the quality of the processed cigarette products.

[0022] The one-way ANOVA decomposes the total sum of squares into between-group and within-group sums of squares based on the additivity of the total sum of squares. The between-group sum of squares reflects the influence of factors on the experimental results, while the within-group sum of squares reflects the influence of errors on the experimental results.

[0023] Preferably, the analysis of positional effect variance and divergence effect variance of the physical indicators of the cigarette includes:

[0024] According to the formula Calculate the arithmetic mean of each quality index of the sample in each test, as the basis for position effect analysis, where x ij Let n be the measured value of a certain quality index of the sample in the i-th test and the j-th test; i The actual number of data points extracted in each experiment. For the i-th trial n i The average value of a certain quality indicator of a sample.

[0025] Preferably, the step of performing position effect variance analysis and divergence effect variance analysis on the physical indicators of the cigarette further includes:

[0026] According to the formula Calculate the natural logarithm of the variance of each quality index of the sample in each test, as the basis for divergence effect analysis, where, For n i The natural logarithm of the variance of a certain quality indicator of a sample.

[0027] Preferred options also include:

[0028] Using χ 2 The test statistic is used to evaluate the stability of the quality of a single batch of rolls and packages. The test statistic is: Obeying χ 2 (n-1), For the population variance, s 2 This represents the sample variance.

[0029] Preferred options also include:

[0030] The two-sample F-test was used to evaluate the stability of the quality of the two batches of rolls. The F-test method is as follows: The expression follows the formula F(n1-1, n2-1), where F is the test statistic. and The variance represents the sample variance for the two batches.

[0031] Preferred options also include:

[0032] To evaluate the stability of the quality of multiple batches of rolls, the F-test is used to test the maximum and minimum variances in a set of variances. If there is no significant difference between the two, the entire set of variances is considered to belong to the same population. If there is a significant difference between the two, pairwise comparisons are required, and the test statistics are calculated separately.

[0033] This invention provides a method for evaluating the quality of cigarette rolling and packaging. It involves multiple samplings of cigarettes from the same batch, obtaining data on individual cigarette weight, draw resistance, circumference, hardness, length, total ventilation rate, and hardness. The rolling and packaging quality is then judged based on the average value of each indicator. This method addresses the common quality problems in existing cigarette rolling machines, such as strip slippage, excessive weight, and empty ends, which prevent operators from quantitatively assessing the severity of quality issues. It provides an accurate overall evaluation of the machine's operation, enabling rapid risk elimination, reduced production costs, and improved product quality. Attached Figure Description

[0034] To more clearly illustrate the specific embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below.

[0035] Figure 1 This is a schematic diagram of a method for evaluating the quality of cigarette packs provided by the present invention. Detailed Implementation

[0036] To enable those skilled in the art to better understand the embodiments of the present invention, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and implementation methods.

[0037] To address the current problem of not being able to quantitatively assess the quality of cigarettes produced by cigarette rolling machines, this invention provides a method for evaluating the quality of cigarette rolling and packaging. This method solves the problem that existing cigarette rolling machines are prone to quality issues such as running cigarettes, excessive weight, and empty ends during the rolling and packaging process, which prevent operators from quantitatively assessing the severity of the quality problems. This method can accurately provide an overall evaluation of the machine's operation, thereby quickly eliminating risks, reducing production costs, and improving product quality.

[0038] like Figure 1 As shown, a method for evaluating the quality of cigarette packs includes:

[0039] S1: Take multiple samples of the same batch of cigarettes that are being produced and obtain sample data corresponding to various physical indicators of the cigarettes. The physical indicators include: single cigarette mass, draw resistance, circumference, hardness, length, total ventilation rate of the cigarettes, and cigarette hardness.

[0040] S2: Calculate the average value of each indicator based on the sample data of the physical indicators, and calculate the variance, standard deviation and coefficient of variation of each indicator based on the average value and the design standard value, so as to determine whether each indicator is within the range specified by the standard.

[0041] S3: If yes, the stability of the cigarette pack quality meets the design requirements; otherwise, perform position effect variance analysis and divergence effect variance analysis on the physical indicators of the cigarette to determine the influencing factors of the cigarette quality stability.

[0042] In one embodiment, 50 cigarettes were sampled each time, for a total of 5 times (each time with a 1-minute interval), to obtain the corresponding single cigarette mass, draw resistance, circumference, hardness, length, total ventilation rate, and cigarette hardness. Test results: The single cigarette mass was all within the range of (0.885±0.080) g, very close to the design value of 0.885 g; the draw resistance was within the range of (1030±200) Pa, with an average draw resistance deviation of ≤51 Pa, slightly higher than the standard requirement of ≤46 Pa, and an average draw resistance of 1035 Pa, close to the design value of 1030 Pa; the circumference, hardness, length, and other physical indicators were also controlled within the standard range, and the average values ​​were close to the design requirements, indicating that the stability of the cigarette pack quality met the design requirements.

[0043] The experimental results were statistically analyzed using position effect and divergence effect analysis methods. Position effect analysis evaluated the influence of experimental factors on the central tendency (mean value) of each evaluation index, while divergence effect analysis evaluated the influence of experimental factors on the dispersion (fluctuation) of each evaluation index. Position effect and divergence effect analyses were used to identify the influence of each experimental factor (including left chamber negative pressure / Kpa, right chamber negative pressure / Kpa, needle roller speed / Hz, conveyor roller speed / Hz, lower conveyor belt speed / Hz, and leveler) on cigarette quality (including cigarette weight, draw resistance, hardness, circumference, and end burnt amount).

[0044] This method compares the single cigarette weight, draw resistance, circumference, hardness, length, total ventilation rate, and hardness of the cigarette with the corresponding design standard values ​​to determine whether the cigarette packing quality meets the requirements. It can accurately provide an overall evaluation of the unit's operation, thereby quickly eliminating risks, reducing production costs, and improving product quality.

[0045] The method also includes:

[0046] The overall average values ​​of the single cigarette weight, draw resistance, circumference, hardness and length of each batch of cigarettes are compared with the corresponding design standard values. The consistency of the quality of each batch of cigarette packs is evaluated by judging whether there is a statistically significant difference between the two.

[0047] If there is a statistically significant difference between the two, it indicates that the quality indicators of this batch of rolls and packages are inconsistent with the standard design values;

[0048] If there is no statistically significant difference between the two, it indicates that the quality indicators of this batch of rolls are consistent with the standard design values.

[0049] Furthermore, the comparison of the overall average values ​​of the individual cigarette weight, draw resistance, circumference, hardness, and length of each batch with the corresponding design standard values ​​includes:

[0050] The consistency of quality of a single batch of rolls and packages is evaluated by using the single population mean t-test to assess the consistency between the quality of a single batch of rolls and packages and the standard design value.

[0051] t-test statistic: in, s is the population mean, s is the population standard deviation, μ0 is the population mean to be tested, and n is the sample size.

[0052] Specifically, for evaluating the consistency of quality in a single batch of roll packages, the overall standard deviation of quality in a single batch cannot be accurately determined under normal circumstances, and in practical evaluation applications, the sample size may vary from large to small. Therefore, the t-test of the single population mean is used to evaluate the consistency of quality in a single batch of roll packages with the standard design value, as follows:

[0053] t-test statistic:

[0054] Double-tail inspection: used to determine whether the quality of a single batch of rolls / packages is consistent with the standard design value.

[0055] Single-tail inspection: used to determine whether the average quality (center of distribution) of a single batch of rolls is greater than or less than the standard design value.

[0056] Significance level: Generally, α = 0.05, which is a confidence level of 95%.

[0057] Statistical analysis tools: Minitab statistical software or Excel statistical functions.

[0058] Furthermore, the comparison of the overall average values ​​of the individual cigarette weight, draw resistance, circumference, hardness, and length of each batch with the corresponding design standard values ​​also includes:

[0059] To evaluate the consistency of quality between two batches of roll packaging, a two-sample t-test was used.

[0060] Two-sample t-test statistic: in, and Let d0 be the population mean corresponding to the two samples, d0 be the hypothetical difference between the two population means, n1 and n2 be the number of samples corresponding to the first and second samples respectively, and s1 and s2 be the standard deviations of samples corresponding to the first and second samples respectively.

[0061] Specifically, the consistency evaluation of the quality of two batches of cigarette packs is to evaluate whether there is a statistically significant difference in the average value (center of mass distribution) of a certain quality indicator of the cigarette pack (such as single weight, draw resistance, circumference, hardness or length) between two different production batches: if there is a statistically significant difference, it indicates that the consistency of that quality indicator of the cigarette pack between the two different production batches is poor; if there is no statistically significant difference, it indicates that the consistency of that quality indicator of the cigarette pack is good.

[0062] Based on the characteristics of sampling in-process cigarette products, the two-sample t-test (i.e., grouped data t-test) method is suitable for evaluating the consistency of quality between two batches of cigarette packs.

[0063] Two-sample t-test statistic (equal variance):

[0064] in,

[0065] Two-sample t-test statistic (heteroscedasticity):

[0066]

[0067] When using a two-sample t-test to evaluate the consistency of quality indicators between two batches of packages, it is essential to first determine whether the variances of the quality indicators for the two batches are the same. This will help determine whether to use an equal-variance two-sample t-test or a heteroscedastic two-sample t-test. In practice, a heteroscedastic two-sample t-test can be directly chosen. In this case, the precision of the test may be slightly reduced, but generally, it will not have a significant impact on the evaluation results.

[0068] Furthermore, the comparison of the overall average values ​​of the individual cigarette weight, draw resistance, circumference, hardness, and length of each batch with the corresponding design standard values ​​also includes:

[0069] To evaluate the consistency of quality across multiple batches of rolls and packages, multiple population mean tests were used. First, different production batches were considered as one factor, and the number of different production batches was regarded as the level number of the factor.

[0070] Sampling inspections were conducted on any three or more different production batches of cigarette products. One-way ANOVA was used to infer whether the factor "different production batches" had a statistically significant impact on the quality of the processed cigarette products.

[0071] The one-way ANOVA decomposes the total sum of squares into between-group and within-group sums of squares based on the additivity of the total sum of squares. The between-group sum of squares reflects the influence of factors on the experimental results, while the within-group sum of squares reflects the influence of errors on the experimental results.

[0072] Furthermore, the position effect variance analysis and divergence effect variance analysis of the physical indicators of the cigarette include:

[0073] According to the formula Calculate the arithmetic mean of each quality index of the sample in each test, as the basis for position effect analysis, where x ij Let n be the measured value of a certain quality index of the sample in the i-th test and the j-th test; i x represents the actual number of data points extracted in each experiment. i For the i-th trial n i The average value of a certain quality indicator of a sample.

[0074] Furthermore, the analysis of positional effect variance and divergence effect variance of the physical indicators of the cigarette further includes:

[0075] According to the formula Calculate the natural logarithm of the variance of each quality index of the sample in each test, as the basis for divergence effect analysis, where, For n i The natural logarithm of the variance of a certain quality indicator of a sample.

[0076] Furthermore, the method also includes:

[0077] Using χ 2 The test statistic is used to evaluate the stability of the quality of a single batch of rolls and packages. The test statistic is: Obeying χ 2 (n-1), For the population variance, s 2 This represents the sample variance.

[0078] Given a significance level α, then:

[0079] H0:

[0080] H1:

[0081] The verification rule is: when If H0 is rejected, then H0 cannot be rejected.

[0082] Furthermore, the method also includes:

[0083] The two-sample F-test was used to evaluate the stability of the quality of the two batches of rolls. The F-test method is as follows: The expression follows the formula F(n1-1, n2-1), where F is the test statistic. and The variance represents the sample variance for the two batches.

[0084] Given a significance level α, then:

[0085] H0:

[0086] H1:

[0087] The test rule is: reject H0 when F≥F(n1-1,n2-1), otherwise H0 cannot be rejected.

[0088] The method also includes: evaluating the stability of the quality of multiple batches of rolls and packages, using the F test to test the maximum and minimum variances in a set of variances. If there is no significant difference between the two, the entire set of variances is considered to belong to the same population. If there is a significant difference between the two, pairwise comparisons are required, and test statistics are calculated separately.

[0089] Therefore, this invention provides a method for evaluating the quality of cigarette rolling and packaging. It involves multiple samplings of cigarettes from the same batch, obtaining data on individual cigarette weight, draw resistance, circumference, hardness, length, total ventilation rate, and hardness. The rolling and packaging quality is then judged based on the average value of each indicator. This method solves the problem of existing cigarette rolling machines easily encountering quality issues such as strip slippage, excessive weight, and empty ends during the rolling process. These issues prevent operators from quantitatively assessing the severity of quality problems. The invention provides an accurate overall evaluation of the machine's operation, thereby quickly eliminating risks, reducing production costs, and improving product quality.

[0090] The structure, features, and effects of the present invention have been described in detail above with reference to the embodiments shown in the figures. The above description is only a preferred embodiment of the present invention, but the present invention is not limited to the scope of implementation shown in the figures. Any changes made in accordance with the concept of the present invention, or equivalent embodiments modified to have equivalent changes, shall be within the protection scope of the present invention as long as they do not exceed the spirit covered by the specification and figures.

Claims

1. A method for evaluating the quality of cigarette packs, characterized in that, include: Multiple samples were taken from the same batch of cigarettes in production, and sample data corresponding to various physical indicators of the cigarettes were obtained. The physical indicators include: single cigarette mass, draw resistance, circumference, hardness, length, total ventilation rate of the cigarette and hardness of the cigarette. The average value of each physical index is calculated based on the sample data, and the variance, standard deviation and coefficient of variation of each index are calculated based on the average value and the design standard value to determine whether each index is within the range specified by the standard. If so, the stability of the cigarette pack quality meets the design requirements; otherwise, position effect variance analysis and divergence effect variance analysis are performed on the physical indicators of the cigarette to determine the influencing factors of the stability of the cigarette quality. The experimental results were statistically analyzed using position effect ANOVA and divergence effect ANOVA to identify the influence of each experimental factor on the quality of cigarettes. Position effect ANOVA was used to evaluate the influence of the experimental factors on the central tendency of each index, while divergence effect ANOVA was used to evaluate the influence of the experimental factors on the dispersion of each index. The experimental factors included: negative pressure in the left and right air chambers, needle roller speed, conveyor roller speed, lower conveyor belt speed, and leveling device. The overall average values ​​of the single cigarette weight, draw resistance, circumference, hardness and length of each batch of cigarettes are compared with the corresponding design standard values. The consistency of the quality of each batch of cigarette packs is evaluated by judging whether there is a statistically significant difference between the two. If there is a statistically significant difference between the two, it indicates that the quality indicators of this batch of rolls and packages are inconsistent with the standard design values; If there is no statistically significant difference between the two, it indicates that the quality indicators of this batch of rolls are consistent with the standard design values.

2. The method for evaluating the quality of cigarette packs according to claim 1, characterized in that, The comparison of the overall average values ​​of individual cigarette weight, draw resistance, circumference, hardness, and length from each batch with the corresponding design standard values ​​includes: The consistency of quality of a single batch of rolls and packages is evaluated by using the single population mean t-test to assess the consistency between the quality of a single batch of rolls and packages and the standard design value. t-test statistic: ,in, s is the population mean, and s is the population standard deviation. Let n be the population mean to be tested, and n be the sample size.

3. The method for evaluating the quality of cigarette packs according to claim 2, characterized in that, The comparison of the overall average values ​​of the individual cigarette weight, draw resistance, circumference, hardness, and length of each batch with the corresponding design standard values ​​also includes: To evaluate the consistency of quality between two batches of roll packaging, a two-sample t-test was used. Two-sample t-test statistic: ,in, , and This represents the population mean corresponding to two samples. Let n1 and n2 be the hypothetical difference between the two population means, and let s1 and s2 be the number of samples corresponding to the first and second samples, respectively. Let s1 and s2 be the standard deviations of the first and second samples, respectively.

4. The method for evaluating the quality of cigarette packs according to claim 3, characterized in that, The comparison of the overall average values ​​of the individual cigarette weight, draw resistance, circumference, hardness, and length of each batch with the corresponding design standard values ​​also includes: To evaluate the consistency of quality across multiple batches of rolls and packages, multiple population mean tests were used. First, different production batches were considered as one factor, and the number of different production batches was regarded as the level number of the factor. Sampling inspections were conducted on any three or more different production batches of cigarette products. One-way ANOVA was used to infer whether the factor "different production batches" had a statistically significant impact on the quality of the processed cigarette products. The one-way ANOVA decomposes the total sum of squares into between-group and within-group sums of squares based on the additivity of the total sum of squares. The between-group sum of squares reflects the influence of factors on the experimental results, while the within-group sum of squares reflects the influence of errors on the experimental results.

5. The method for evaluating the quality of cigarette packs according to claim 4, characterized in that, The position effect variance analysis and divergence effect variance analysis of the physical indicators of the cigarette include: According to the formula Calculate the arithmetic mean of each quality index of the sample in each test, as the basis for position effect analysis, where, Let be the measured value of a certain quality index of the sample in the i-th test and the j-th test. The actual number of data points extracted in each experiment. For the i-th trial The average value of a certain quality indicator of a sample.

6. The method for evaluating the quality of cigarette packs according to claim 5, characterized in that, The analysis of positional effect variance and divergence effect variance of the physical indicators of the cigarette also includes: According to the formula Calculate the natural logarithm of the variance of each quality index of the sample in each test, as the basis for divergence effect analysis, where, for The natural logarithm of the variance of a certain quality indicator of a sample.

7. The method for evaluating the quality of cigarette packs according to claim 6, characterized in that, Also includes: use The test statistic is used to evaluate the stability of the quality of a single batch of rolls and packages. The test statistic is: obey , For the population variance, This represents the sample variance.

8. The method for evaluating the quality of cigarette packs according to claim 7, characterized in that, Also includes: The two-sample F-test was used to evaluate the stability of the quality of the two batches of rolls. The F-test method is as follows: ,obey F is the test statistic. and The variance represents the sample variance for the two batches.

9. The method for evaluating the quality of cigarette packs according to claim 8, characterized in that, Also includes: To evaluate the stability of the quality of multiple batches of rolls, the F-test is used to test the maximum and minimum variances in a set of variances. If there is no significant difference between the two, the entire set of variances is considered to belong to the same population. If there is a significant difference between the two, pairwise comparisons are required, and the test statistics are calculated separately.

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