Method for evaluating the suitability of a cigarette wrapping material to a cigarette wrapping machine

Abstract

The present application relates to a kind of cigarette roll packing auxiliary material on-machine adaptability evaluation method, belong to cigarette raw and auxiliary material on-machine adaptability evaluation field, and by collecting production, equipment, quality and so on Index, establish adaptability evaluation model, calculate comprehensive score by evaluation model, objectively evaluate the on-machine adaptability of different auxiliary material manufacturers roll packing auxiliary material.There is higher objectivity, and score is obtained by model calculation, and visual data comparison can be carried out between different factory suppliers auxiliary material, solve the fluctuation caused by traditional subjective evaluation.

Description

Technical Field

[0001] This invention belongs to the field of machine adaptability evaluation of cigarette raw and auxiliary materials, specifically, it relates to an evaluation method for the machine adaptability of cigarette packaging auxiliary materials. Background Technology

[0002] The machine adaptability of cigarette raw and auxiliary materials refers to the impact of cigarette packaging materials such as trademarks, liners, BOPP film, carton, tipping paper, and cigarette paper on equipment efficiency, product quality, and production costs when used in cigarette rolling and packaging machines. Better machine adaptability of auxiliary materials means less impact on the manufacturing process and greater benefits for product production. Cigarette factories are supplied with cigarette packaging materials by different auxiliary material manufacturers. Although all cigarette packaging materials have comprehensive quality control standards, differences in production equipment, production environment, and process quality control levels among auxiliary material manufacturers lead to significant fluctuations in the machine adaptability of similar packaging materials from different manufacturers. These fluctuations affect the manufacturing process to some extent, restricting equipment efficiency, production costs, and product quality.

[0003] Currently, the evaluation of the machine adaptability of similar auxiliary materials from different manufacturers relies more on the subjective evaluation of operators and repair personnel, and no objective and quantifiable evaluation method has been formed. Summary of the Invention

[0004] To overcome the problems existing in the background technology, this invention provides an evaluation method for the adaptability of auxiliary materials from different manufacturers to the production process. This patent constructs an evaluation framework by collecting equipment, production, and quality data during the production process, forming a method applicable to evaluating the adaptability of auxiliary materials from different suppliers. Because this method uses equipment to collect data, it has high objectivity, and by calculating scores through a model, it allows for visual data comparison between auxiliary materials from different suppliers, thus solving the fluctuations caused by traditional subjective evaluations.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution:

[0006] A method for evaluating the machine adaptability of cigarette packaging auxiliary materials includes the following steps:

[0007] S1 uses production status, equipment status, and quality status as primary indicators;

[0008] S2. The primary indicator of production status includes the secondary indicators of output and consumption. Output is represented by the tertiary indicator of output ratio, and its characteristics, extreme values ​​and weights are defined. Consumption is represented by the tertiary indicator of auxiliary material consumption ratio, and its characteristics, extreme values ​​and weights are defined.

[0009] S3. The primary indicator of equipment status includes the secondary indicators of vehicle speed and downtime; vehicle speed is composed of the tertiary indicators of total downtime rate, critical downtime rate, and critical downtime percentage; downtime is composed of the tertiary indicators of average vehicle speed, average speed below full speed, and percentage of speed below full speed; their characteristics, extreme values, and weights are defined respectively.

[0010] S4. The quality status of the first-level indicator includes the second-level indicators of equipment defect elimination and process sampling inspection; the equipment defect elimination is characterized by the third-level indicator of yield rate, and its characteristics, extreme values ​​and weights are defined respectively; the process sampling inspection is characterized by the third-level indicator of defect rate, and its characteristics, extreme values ​​and weights are also defined.

[0011] S5. By integrating indicators at all levels, establish an evaluation model for the adaptability of auxiliary materials to machine operation. Calculate the comprehensive score through the evaluation model to objectively evaluate the adaptability of roll-packaged auxiliary materials from different manufacturers to machine operation.

[0012] Furthermore, the primary indicators of production status, equipment status, and quality status mentioned in step S1 are obtained from the data acquisition system of the cigarette rolling and packaging equipment and process sampling inspection during the actual production process.

[0013] Furthermore, in step S2, the production ratio is calculated as: actual production / theoretical production, with the characteristic of being expected to be high; the auxiliary material consumption ratio is calculated as: (actual auxiliary material consumption - actual production) / actual production, with the characteristic of being expected to be low.

[0014] Furthermore, in step S3, the calculation method for the total downtime rate is: total downtime / theoretical production time, with the characteristic of a low expectation; the calculation method for the critical downtime rate is: critical downtime / theoretical production time, with the characteristic of a low expectation; the calculation method for the critical percentage is: critical downtime / total downtime, with the characteristic of a low expectation; the vehicle speed is composed of three levels of indicators, where the calculation method for the average vehicle speed is: the average operating speed of the equipment during the production period, with the characteristic of a high expectation; the calculation method for the average non-full speed is: the average speed of the equipment that did not reach the theoretical maximum speed during the production period, with the characteristic of a high expectation; the calculation method for the non-full speed percentage is: the frequency of collection points that did not reach the theoretical maximum speed during the production period / the frequency of collection points that reached the maximum speed, with the characteristic of a low expectation.

[0015] Furthermore, in step S4, the yield rate is calculated as: 1 - (critical defect elimination / actual output), with a high expected yield; the defect rate is calculated as: number of defects sampled / total number of samples sampled, with a low expected yield.

[0016] Furthermore, the output ratio has an upper limit of 95% and a lower limit of 85%, with a weight of 12%; the auxiliary material consumption ratio has an upper limit of 0.20 and a lower limit of 0.60, with a weight of 12%; the total downtime rate has an upper limit of 5% and a lower limit of 30%, with a weight of 5%; the critical downtime rate has an upper limit of 0% and a lower limit of 5%, with a weight of 8%; the critical percentage has an upper limit of 1% and a lower limit of 50%, with a weight of 5%; the average machine speed has an upper limit of 600 and a lower limit of 0, with a weight of 5%; the average non-full speed speed has an upper limit of 600 and a lower limit of 0, with a weight of 5%; the yield rate has an upper limit of 99.99% and a lower limit of 99.73%, with a weight of 20%; and the defect rate has an upper limit of 0% and a lower limit of 10%, with a weight of 20%.

[0017] Furthermore, according to claim 6, the evaluation method for the machine adaptability of cigarette packaging auxiliary materials is characterized in that: the evaluation model for the machine adaptability of auxiliary materials includes:

[0018] (1) When the calculation index is a large-scale characteristic:

[0019]

[0020] (2) When the calculation index is the small-scale characteristic:

[0021]

[0022] (3) Evaluation model overall score:

[0023]

[0024] In equations (1)-(2), X i S represents the evaluation index score, C represents the actual value, A represents the upper limit value, and B represents the lower limit value; in equation (3), S t This represents the overall evaluation score of the excipient to be evaluated, where n is the number of indices, i represents the index or excipient number, and W... i X represents the weight of each evaluation indicator. i This represents the scores of each evaluation indicator.

[0025] The beneficial effects of this invention are:

[0026] Prior to this invention, the evaluation of the machine adaptability of packaging accessories in production workshops mainly relied on feedback from machine operators, which was highly subjective and easily influenced by emotions and inertia, thus having limitations. The machine adaptability evaluation method for packaging accessories provided by this invention primarily uses equipment production data. Through the extraction and analysis of production, equipment, and quality-related data, it can objectively and accurately characterize the machine adaptability of accessories, providing a quantifiable basis for evaluating the quality level of accessories in the packaging production process, and thus contributing to improving the level of packaging manufacturing. Attached Figure Description

[0027] Figure 1This is a flowchart illustrating the machine adaptability evaluation method for roll packaging auxiliary materials provided in the embodiments of the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and beneficial effects of the present invention clearer, the preferred embodiments of the present invention will be described in detail below to facilitate understanding by those skilled in the art.

[0029] Example 1

[0030] A method for evaluating the machine adaptability of cigarette packaging auxiliary materials includes the following steps:

[0031] S1 uses production status, equipment status, and quality status as primary indicators;

[0032] S2. The primary indicator of production status includes the secondary indicators of output and consumption. Output is represented by the tertiary indicator of output ratio, and its characteristics, extreme values ​​and weights are defined. Consumption is represented by the tertiary indicator of auxiliary material consumption ratio, and its characteristics, extreme values ​​and weights are defined.

[0033] S3. The primary indicator of equipment status includes the secondary indicators of vehicle speed and downtime; vehicle speed is composed of the tertiary indicators of total downtime rate, critical downtime rate, and critical downtime percentage; downtime is composed of the tertiary indicators of average vehicle speed, average speed below full speed, and percentage of speed below full speed; their characteristics, extreme values, and weights are defined respectively.

[0034] S4. The quality status of the first-level indicator includes the second-level indicators of equipment defect elimination and process sampling inspection; the equipment defect elimination is characterized by the third-level indicator of yield rate, and its characteristics, extreme values ​​and weights are defined respectively; the process sampling inspection is characterized by the third-level indicator of defect rate, and its characteristics, extreme values ​​and weights are also defined.

[0035] S5. By integrating indicators at all levels, establish an evaluation model for the adaptability of auxiliary materials to machine operation. Calculate the comprehensive score through the evaluation model to objectively evaluate the adaptability of roll-packaged auxiliary materials from different manufacturers to machine operation.

[0036] In step S1, the primary indicators of production status, equipment status, and quality status are obtained from the data acquisition system of the cigarette rolling and packaging equipment and process sampling inspection during the actual production process.

[0037] In step S2, the production ratio is calculated as: actual production / theoretical production, with the characteristic of being expected to be high; the auxiliary material consumption ratio is calculated as: (actual auxiliary material consumption - actual production) / actual production, with the characteristic of being expected to be low.

[0038] In step S3, the calculation method for total downtime rate is: total downtime / theoretical production time, with a tendency to be low; the calculation method for critical downtime rate is: critical downtime / theoretical production time, with a tendency to be low; the calculation method for critical percentage is: critical downtime / total downtime, with a tendency to be low; vehicle speed is composed of three levels of indicators, where the calculation method for average vehicle speed is: average equipment operating speed during the production period, with a tendency to be high; the calculation method for non-full speed average is: average speed during the production period where the equipment operating speed did not reach the theoretical maximum speed, with a tendency to be high; and the calculation method for non-full speed percentage is: frequency of collection points that did not reach the theoretical maximum speed during the production period / frequency of collection points that reached the maximum speed, with a tendency to be low.

[0039] In step S4, the yield rate is calculated as: 1 - (critical defect elimination / actual output), with a high expected yield. The defect rate is calculated as: number of defects sampled / total number of samples sampled, with a low expected defect rate.

[0040] Among them, the output ratio has an upper limit of 95% and a lower limit of 85%, with a weight of 12%; the auxiliary material consumption ratio has an upper limit of 0.20 and a lower limit of 0.60, with a weight of 12%; the total downtime rate has an upper limit of 5% and a lower limit of 30%, with a weight of 5%; the critical downtime rate has an upper limit of 0% and a lower limit of 5%, with a weight of 8%; the critical percentage has an upper limit of 1% and a lower limit of 50%, with a weight of 5%; the average machine speed has an upper limit of 600 and a lower limit of 0, with a weight of 5%; the average non-full speed speed has an upper limit of 600 and a lower limit of 0, with a weight of 5%; the yield rate has an upper limit of 99.99% and a lower limit of 99.73%, with a weight of 20%; and the defect rate has an upper limit of 0% and a lower limit of 10%, with a weight of 20%.

[0041] The method for evaluating the machine adaptability of cigarette packaging auxiliary materials according to claim 6 is characterized in that: the evaluation model for the machine adaptability of auxiliary materials includes:

[0042] (1) When the calculation index is a large-scale characteristic:

[0043]

[0044] (2) When the calculation index is the small-scale characteristic:

[0045]

[0046] (3) Evaluation model overall score:

[0047]

[0048] In equations (1)-(2), X i S represents the evaluation index score, C represents the actual value, A represents the upper limit value, and B represents the lower limit value; in equation (3), S tThis represents the overall evaluation score of the excipient to be evaluated, where n is the number of indices, i represents the index or excipient number, and W... i X represents the weight of each evaluation indicator. i This represents the scores of each evaluation indicator.

[0049] Example 2,

[0050] Using the trademark used by my cigarette factory's Brand A as the test object, we conducted the verification of the evaluation model for this invention. The test plan is shown in Table 1:

[0051] Table 1 Experimental Plan

[0052]

[0053] According to the method described in Example 1 and Figure 1 The process evaluates the adaptability of trademarks to the system, and the indicator models are as follows:

[0054] Table 2. Weights and upper and lower limits of each evaluation indicator

[0055]

[0056]

[0057] Information on the packaging machine was collected during the test, and the evaluation was conducted from three dimensions: production, equipment, and quality. The evaluation scores for each indicator are shown in Table 3.

[0058] Table 3 Evaluation scores of various indicators for different auxiliary material manufacturers' trademarks

[0059]

[0060] The comparison revealed differences in the evaluation scores of auxiliary materials from different manufacturers on the same packaging machine. Based on the evaluation model scores in Table 3, the order of adaptability of trademark A on this packaging machine from best to worst is: HT > HQ > EJ > GW > MD > TY > LD > HX.

[0061] By using the auxiliary material adaptability evaluation method, we can not only provide a more objective quantitative basis for evaluating the adaptability of auxiliary materials among manufacturers, but also make packaging machines more targeted in terms of auxiliary material supply.

[0062] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made to it in form and detail without departing from the scope defined by the claims of the present invention.

Claims

1. A method for evaluating the machine adaptability of cigarette packaging auxiliary materials, characterized in that, Includes the following steps: S1 uses production status, equipment status, and quality status as primary indicators; S2. The primary indicator of production status includes the secondary indicators of output and consumption. Output is represented by the tertiary indicator of output ratio, and its characteristics, extreme values ​​and weights are defined. Consumption is represented by the tertiary indicator of auxiliary material consumption ratio, and its characteristics, extreme values ​​and weights are defined. S3. The primary indicator of equipment status includes the secondary indicators of vehicle speed and downtime; vehicle speed is composed of the tertiary indicators of total downtime rate, critical downtime rate, and critical downtime percentage; downtime is composed of the tertiary indicators of average vehicle speed, average speed below full speed, and percentage of speed below full speed; their characteristics, extreme values, and weights are defined respectively. S4. The primary indicator of quality includes the secondary indicators of equipment defect elimination and process sampling inspection; Equipment defect elimination is characterized by a three-level indicator, yield rate, with its characteristics, extreme values, and weights defined respectively; process sampling inspection is characterized by a three-level indicator, defect rate, with its characteristics, extreme values, and weights also defined. S5. By integrating indicators at all levels, establish an evaluation model for the adaptability of auxiliary materials to machine use. Calculate the comprehensive score through the evaluation model to objectively evaluate the adaptability of roll-packaged auxiliary materials from different manufacturers to machine use. The evaluation model for the adaptability of auxiliary materials to the machine includes: (1) When the calculation index is the large-scale characteristic: — Evaluation indicator scores C — Actual value; A — Upper limit; B — Lower limit value; (2) When the calculation index is the small-scale characteristic: (3) Evaluation model comprehensive score: — The overall score of the excipients to be evaluated; n — Number of indicators; — Indicator or auxiliary material serial number; — The weight of each evaluation indicator; — Scores for each evaluation indicator; Among them, the output ratio is 95% of the upper limit and 85% of the lower limit, with a weight of 12%, and the indicator characteristic is expected to be large. The upper limit of auxiliary material consumption ratio is 0.20, the lower limit is 0.60, the weight is 12%, and the indicator characteristic is expected to be small. The overall downtime rate has an upper limit of 5%, a lower limit of 30%, a weight of 5%, and the indicator characteristic is expected to be low. The key downtime rate has an upper limit of 0%, a lower limit of 5%, a weight of 8%, and the indicator's characteristics suggest low potential. The key percentage has an upper limit of 1%, a lower limit of 50%, a weight of 5%, and the indicator's characteristic is low potential. The average vehicle speed has an upper limit of 600 and a lower limit of 0, with a weight of 5%, and the indicator characteristic is high potential. The upper limit of the non-full speed average value is 600, the lower limit is 0, the weight is 5%, and the indicator characteristic is expected to be large. The yield rate has an upper limit of 99.99%, a lower limit of 99.73%, a weight of 20%, and the indicator is expected to be high. The upper limit of the defect rate is 0%, the lower limit is 10%, the weight is 20%, and the characteristic of the indicator is expected to be small.

2. The method for evaluating the machine adaptability of cigarette packaging auxiliary materials according to claim 1, characterized in that: The primary indicators of production status, equipment status, and quality status mentioned in step S1 are obtained from the data acquisition system of the cigarette rolling and packaging equipment and process sampling inspection during the actual production process.

3. The method for evaluating the machine adaptability of cigarette packaging auxiliary materials according to claim 1, characterized in that: In step S2, the production ratio is calculated as: actual production / theoretical production; the auxiliary material consumption ratio is calculated as: (actual auxiliary material consumption - actual production) / actual production.

4. The method for evaluating the machine adaptability of cigarette packaging auxiliary materials according to claim 1, characterized in that: In step S3, the calculation method for the total downtime rate is: total downtime / theoretical production time; The critical downtime rate is calculated as: critical downtime / theoretical production time. The key percentage is calculated as: key downtime / total downtime; vehicle speed is composed of three levels of indicators, of which the average vehicle speed is calculated as: the average operating speed of the equipment during the production period; the non-full speed average is calculated as: the average speed of the equipment during the production period when the operating speed did not reach the theoretical maximum speed. The calculation method for the non-full speed percentage is: the frequency of sampling points that did not reach the theoretical maximum speed during the production period / the frequency of sampling points that reached the maximum speed.

5. The method for evaluating the machine adaptability of cigarette packaging auxiliary materials according to claim 1, characterized in that: In step S4, the yield rate is calculated as: 1 - (critical defect elimination / actual output); the defect rate is calculated as: number of defects sampled / total number of samples.

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