Plastic bag production monitoring system based on Internet of Things

Abstract

The invention discloses a plastic bag production monitoring system based on the Internet of Things, relates to the technical field of plastic bag production, and aims to solve the problems that abnormal conditions in production cannot be recognized and adjusted in time, the proportion of a plasticizer in raw materials is lack of fine control, the proportion of the plasticizer in the plastic bag raw materials is determined, and the production efficiency is improved. The sequence and precision of punching and bag cutting are generally set according to experience, and real-time optimization is difficult to carry out in dynamic production; the introduction of the Internet of Things technology can ensure that each production link has traceable data, the transparency of the production process is improved, errors in manual operation are avoided, the proportion of the plasticizer is dynamically adjusted according to the flexibility and transparency data, the use optimization of the plasticizer is realized, and the production efficiency is improved. The system automatically selects the optimal punching and bag cutting sequence according to real-time data, the production precision is improved, and the consistency and stability of final products in quality are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of plastic bag production, and more specifically, to an Internet of Things-based plastic bag production monitoring system. Background Art

[0002] In the traditional plastic bag production process, manual inspection is mainly relied on. Real-time data of some key parameters and equipment status during the production process cannot be timely fed back to the operators, resulting in low production efficiency and unstable product quality. The Internet of Things-based monitoring system can comprehensively monitor the production line through sensors. Specifically, the sensors can collect multiple parameters involved in the production process, such as the operating status of the machine, production speed, die pressing pressure, etc., and transmit the data to the cloud platform through a wireless network. The cloud platform uses big data analysis technology to monitor the entire production process in real time, timely discover potential problems or production bottlenecks, and provide decision-making support for management personnel.

[0003] The prior art has the following deficiencies:

[0004] The traditional method cannot timely identify and adjust abnormal situations in production, thereby improving production efficiency and product quality. There is a lack of fine control over the proportion of plasticizer in the raw materials. Determining the proportion of plasticizer in the plastic bag raw materials is likely to cause the flexibility of the plastic bag not to meet the requirements or waste resources. The sequence and precision of punching and bag cutting are generally set according to experience, and it is difficult to perform real-time optimization in dynamic production.

[0005] In view of the above problems, the present invention proposes a solution. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an Internet of Things-based plastic bag production monitoring system to solve the problems proposed in the above background art.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] An Internet of Things-based plastic bag production monitoring system, comprising: an information acquisition module, an information processing module, and a process selection module, with signal connections between the modules:

[0009] Information acquisition module: Obtain the stretch rate and light transmittance required for the plastic bag to obtain the flexibility score and transparency score of the plastic bag;

[0010] Information processing module: Determine the proportion of plasticizer in the plastic bag raw materials based on the obtained flexibility and transparency of the plastic bag;

[0011] Process selection module: Obtain the cutting accuracy of the plastic bag and determine the punching and bag cutting sequence in the third process of punching and bag cutting in combination with the proportion of plasticizer in the plastic bag additives.

[0012] In a preferred embodiment, the process design module includes the following:

[0013] Use the control material comparison table to determine the elongation rate to be achieved according to the uses of different plastic bags, denoted as S atual , and calculate the flexibility score based on the maximum and minimum values of the elongation rate. The calculation formula is expressed as: Where: F flexibility represents the flexibility score; S actual represents the actual elongation rate to be achieved; S min represents the minimum elongation rate required in the application of the plastic bag, that is, the minimum value of the elongation rate; S max represents the maximum acceptable elongation rate in the application of the plastic bag, that is, the maximum value of the elongation rate;

[0014] Use the control material comparison table to determine the light transmittance to be achieved according to the uses of different plastic bags, recorded as L actual , and calculate the transparency score by ratio based on the highest light transmittance required in the application of the plastic bag. The calculation formula is expressed as: Where: F transparency represents the transparency score; L actual represents the actually measured light transmittance; L max represents the highest light transmittance required in the application of this plastic bag.

[0015] In a preferred embodiment, the information acquisition module includes the following:

[0016] By changing the proportion of plasticizer in the additive to regulate the flexibility and transparency of the plastic bag, the formula for calculating the proportion of plasticizer in the plastic bag additive using the flexibility score and transparency score is expressed as: P plasticizer = w 1 ·F flexibility + w 2 ·(1 - F transparency ), where: w 1 and w 2 are the weight coefficients of the flexibility score and the transparency score, and w 1 + w 2 = 1, F flexibility is the flexibility score, and F transparency is the transparency score.

[0017] In a preferred embodiment, the information processing module includes the following:

[0018] Use the control material comparison table to determine the required cutting accuracy according to the uses of different plastic bags;

[0019] After the process selection module receives the proportion of the plasticizer in the plastic bag among the plastic bag additives and the cutting accuracy, it defines the proportion of the plasticizer in the plastic bag among the plastic bag additives and the cutting accuracy as input variables, and divides them into different fuzzy sets respectively;

[0020] Define the order of punching and bag cutting in the next plastic bag process as the output variable, and divide it into a fuzzy set;

[0021] Formulate fuzzy rules to describe the influence of the proportion of the plasticizer in the plastic bag among the plastic bag additives and the defined cutting accuracy on the order of punching and bag cutting in the next plastic bag process;

[0022] Conduct fuzzy reasoning according to the fuzzy rules to determine the order of punching and bag cutting in the next plastic bag process of the plastic bag;

[0023] Among them, the fuzzy set division method of the cutting accuracy is as follows: Access the historical database to obtain the cutting accuracies of multiple plastic bag production machines and merge them into a cutting accuracy data set. Set the cutting accuracy threshold using the percentile method according to the cutting accuracy data set. Arrange the data in the cutting accuracy data set from smallest to largest, and set N 1 %, and N 2 % as the percentile ratios, where N 1 % > N 2 .

[0024] The technical effects and advantages of a plastic bag production monitoring system based on the Internet of Things according to the present invention:

[0025] The introduction of Internet of Things technology can ensure that there is traceable data in each production link, improve the transparency and controllability of the production process, and avoid errors in manual operations. Dynamically adjust the proportion of the plasticizer according to the flexibility and transparency data to achieve the optimization of the use of the plasticizer, thereby reducing raw material waste and improving the uniformity of the product. The system automatically selects the best punching and bag cutting order according to real-time data, and adjusts the accuracy of the process according to the proportion of the plasticizer, improving the production accuracy, reducing raw material waste, and also ensuring the consistency and stability of the quality of the final product. Brief Description of the Drawings

[0026] Figure 1 It is a schematic structural diagram of a plastic bag production monitoring system based on the Internet of Things according to the present invention. Detailed Embodiment

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0028] Embodiment 1

[0029] As shown in the present invention Figure 1 a plastic bag production monitoring system based on the Internet of Things is disclosed, including: an information acquisition module, an information processing module, and a process selection module, and the modules are signal-connected to each other.

[0030] Information acquisition module: Obtain the elongation rate and light transmittance required for the plastic bag to obtain the flexibility score and transparency score of the plastic bag;

[0031] Information processing module: Determine the proportion of plasticizer in the plastic bag raw material according to the obtained flexibility and transparency of the plastic bag;

[0032] Process selection module: Obtain the cutting accuracy of the plastic bag and determine the punching and bag cutting sequence in the third process of punching and bag cutting in combination with the proportion of plasticizer in the plastic bag additive.

[0033] The functions of each module are as follows:

[0034] In the information acquisition module, obtain the elongation rate and light transmittance required for the plastic bag to obtain the flexibility score and transparency score of the plastic bag. The specific content includes:

[0035] Use the elongation rate and light transmittance of the plastic bag to obtain the flexibility score and transparency score of the plastic bag respectively, and determine the required flexibility and transparency for making the plastic bag according to the material comparison table. The material comparison table is a tool summarized according to the characteristics and uses of different types of plastic bags, and usually lists information such as common material types of various plastic bags, their characteristics, uses, advantages and disadvantages, etc. It is usually based on the analysis of historical data to determine which materials are suitable for different usage scenarios and ensure that their performance meets the requirements.

[0036] Use the control material comparison table to determine the required elongation rate according to the use of different plastic bags. Flexibility is usually evaluated by the elongation rate of the material, and the score is based on the flexibility level. Since this score is used to comprehensively determine the proportion of plasticizer in the plastic bag additive later, obtain the required elongation rate of the plastic bag, denoted as S actual , and calculate the flexibility score according to the maximum and minimum values of the elongation rate, ensuring that the score range is 0-1, and record the flexibility score of the plastic bag, denoted as F flexibility The calculation formula is expressed as: Among them: F flexibility represents the flexibility score; S actual represents the stretching rate that actually needs to be achieved; S min represents the minimum stretching rate required in the application of plastic bags, that is, the minimum value of the stretching rate; S max represents the maximum stretching rate acceptable in the application of plastic bags, that is, the maximum value of the stretching rate.

[0037] It should be noted that: if the actual stretching rate of the plastic bag is close to the standard maximum value S max , then the flexibility score F flexibility is close to 1. If the actual test result is lower and close to the minimum value S min , then the flexibility score F flexibility is close to 0. The ranges of S min and S max and the value of S actual can be adjusted according to the specific requirements of the plastic bag. Specifically, it can be set by those skilled in the art according to the actual situation and will not be elaborated here.

[0038] Use the control material comparison table to determine the light transmittance that needs to be achieved according to the uses of different plastic bags. Evaluate the transparency through the light transmittance. Usually, optical detection or standardized test methods are adopted. At the same time, the standards for transparency can be changed according to the uses of different plastic bags. For example, for plastic bags used for food or product display, higher transparency is required, and a light transmittance close to 100% may be needed; while for plastic bags used for garbage collection or industrial purposes, lower transparency is required, and low-transparency materials can be used to reduce costs. Score according to the light transmittance level. The scoring range is 0 - 1. The specific scoring rules can be set by technical personnel according to the actual situation and will not be elaborated here, and record the transparency score of the plastic bag, denoted as F transparency .

[0039] The transparency score is measured through the light transmittance. The standards can be adjusted according to different uses (such as food packaging, industrial use, etc.). The calculation formula for the transparency score can be expressed as:

[0040] Among them: F transparency represents the transparency score; L actual represents the actually measured light transmittance; L max represents the maximum light transmittance required in the application of this plastic bag.

[0041] It should be noted that if the actual light transmittance L actual is close to the maximum value L max , then the transparency score F transparency will be close to 1. If the actual light transmittance is low and close to the minimum requirement, then the transparency score Ftransparency will approach 0. Under different uses and requirements, L max can vary. For example, food packaging bags may require a light transmittance close to 100%, while garbage bags and the like can have a lower light transmittance standard.

[0042] In the information processing module, the proportion of plasticizer in the plastic bag additive is determined based on the obtained flexibility score and transparency score of the plastic bag. The specific content includes:

[0043] In the preparation of the raw materials for plastic bags, polyethylene particles and additives need to be prepared. Plastic bags are usually made of polyethylene materials. Additives are used to change the properties of plastic bags. By changing the proportion of plasticizer in the additives, the flexibility and transparency of plastic bags can be regulated. Therefore, the following calculation is used to determine the proportion of the required plasticizer in the plastic bag additive based on the flexibility score and transparency score. The formula can be expressed as: P plasticizer = w 1 ·F flexibility + w 2 ·(1 - F transparency ), where: w 1 and w 2 are the weight coefficients of the flexibility score and transparency score, and w 1 + w 2 = 1, F flexibilty is the flexibility score, and F transparency is the transparency score.

[0044] For example: Suppose there are the following data in the preparation process of the raw materials for plastic bags: the required flexibility score F flexibility = 0.8, the transparency score F transparency = 0.6, the flexibility weight w 1 = 0.7, the transparency weight w 2 = 0.3. Calculate the proportion of plasticizer in the plastic bag additive according to the formula: P plasticizer = w 1 ·F flexibility + w 2 ·(1 - F transparency ) = 0.7×0.8 + 0.3×(1 - 0.6) = 68%, so in this case the proportion of plasticizer in the plastic bag additive is 68%.

[0045] It should be noted that for the flexibility requirements of plastic bags, if the plastic bag requires higher flexibility, more plasticizer may be needed to improve the flexibility score. Therefore, it needs to be adjusted positively in the formula. For the transparency requirements of plastic bags, if the transparency requirement is high (for example, for product display or food packaging), the use of plasticizer should be appropriate to avoid affecting transparency. Therefore, it needs to be adjusted inversely in the formula. w 1 and w2 Jointly determine the proportion of plasticizer in the plastic bag additives, and it is necessary to ensure that this proportion is between 0 and 1. Therefore, it is necessary to ensure that w 1 +w 2 = 1.

[0046] In the process selection module, obtain the cutting accuracy of the plastic bag and determine the punching and bag cutting sequence in the next step of the plastic bag process in combination with the proportion of plasticizer in the plastic bag additives. The specific content includes:

[0047] Cutting accuracy is crucial for the final product quality of plastic bags. Especially during mass production, accuracy has a direct impact on the dimensional consistency and appearance. Cutting accuracy is usually determined according to the size requirements of plastic bags and the capabilities of production equipment. Generally, accuracy requirements are determined at the production process stage, affecting the neatness of the final product. Accuracy can be detected by standard measuring tools and ensure the accuracy of the cutting position. Generally, the cutting accuracy is controlled within a certain error range to ensure the consistency of product specifications. Use the control material comparison table to determine the required cutting accuracy according to the uses of different plastic bags.

[0048] After the process selection module receives the proportion of plasticizer in the plastic bag additives and the cutting accuracy of the plastic bag, define the proportion of plasticizer in the plastic bag additives and the cutting accuracy of the plastic bag as input variables and divide them into different fuzzy sets respectively.

[0049] For example, "Low", "Medium", "High" for the proportion of plasticizer in the plastic bag additives, and "Low", "Medium", "High" for the cutting accuracy.

[0050] Define the punching and bag cutting sequence in the next step of the plastic bag process as the output variable and divide it into a fuzzy set. For example, "Punching", "Cutting" for the punching and bag cutting sequence in the next step of the plastic bag process.

[0051] Formulate a set of fuzzy rules to describe the influence of different input variables on the output variable. The definition of the rules can be based on professional knowledge or obtained through data analysis and experiments. For example:

[0052] Mark the proportion of plasticizer in the plastic bag additives as P plasticizer , mark the cutting accuracy as A, and mark the priority order of punching and bag cutting in the next step of the plastic bag process as Process. Then, it can be defined as

[0053] Rule 1: IF (P plasticizer is Low) AND (B is Low) THEN (Process is Punching)

[0054] Rule 2: IF (P plasticizer is High) AND (B is High) THEN (Process is Cutting) ...

[0056] According to the fuzzy rules, perform fuzzy reasoning to determine the scheme for the sequence of hole punching and bag cutting in the next plastic bag process step.

[0057] It should be noted that the division of fuzzy sets can be adjusted according to the actual situation. For example, although this embodiment takes three fuzzy sets as an example, in fact, the proportion of plasticizer in plastic bag additives, cutting accuracy, and the sequence of hole punching and bag cutting in the next plastic bag process step can be divided into more than three sets to facilitate more accurate adjustment according to different temperatures.

[0058] Furthermore, for the determination of high, medium, and low levels of the proportion of plasticizer in plastic bag additives, thresholds can be set according to the actual situation. For example, when the proportion of plasticizer in plastic bag additives exceeds 80%, it is calibrated as "High". For the determination of high, medium, and low levels of cutting accuracy, thresholds can be designed using the percentile method based on the historical data of each plastic bag production machine. The specific calculation is as follows:

[0059] Access the historical database to obtain the cutting accuracies of multiple plastic bag production machines and combine them into a cutting accuracy dataset. Set the cutting accuracy threshold using the percentile method based on the cutting accuracy dataset. Arrange the data in the cutting accuracy dataset from smallest to largest, and set N 1 % and N 2 % as the percentile ratios, where N 1 % > N 2 %. Calibrate the cutting accuracy exceeding N 1 % as "High", the cutting accuracy between N 1 % and N 2 % as "Medium", and the cutting accuracy below N 2 % as "Low". For example, set the percentile ratios N 1 % and N 2 % to 80% and 20%. Then, calibrate the cutting accuracy exceeding 80% in the cutting accuracy set as "High", the cutting accuracy between 80% and 20% as "Medium", and the cutting accuracy below 20% as "Low".

[0060] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain a formula that is closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0061] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0062] Those of ordinary skill in the art will realize that the modules and algorithm steps of each example described in connection with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and the inventive constraints of the technical solution. A professional technician can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0063] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module.

[0064] As described above, this is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0065] Finally: The above is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should all be included within the protection scope of the present invention.

Claims

1. A plastic bag production monitoring system based on the Internet of Things, characterized in that: include: Information acquisition module, information processing module and process selection module, and signal connections between modules; Information acquisition module: obtain the required stretch rate and light transmittance of the plastic bag to obtain the flexibility score and transparency score of the plastic bag; Information processing module: determine the proportion of plasticizer in the raw materials of the plastic bag according to the flexibility and transparency of the plastic bag; Process selection module: obtains the cutting accuracy of plastic bags and determines the order of punching and bag cutting in the third process of punching and bag cutting based on the proportion of plasticizer in plastic bag additives.

2. According to claim 1, a plastic bag production monitoring system based on the Internet of Things is characterized by: Use the reference material comparison table to determine the required stretch rate according to the purpose of different plastic bags, recorded as S actual , and the flexibility score is calculated based on the maximum and minimum values ​​of the stretch rate. The calculation formula is expressed as: Among them: F flexibility represents the flexibility score; S actual Represents the actual stretch rate that needs to be achieved; S min Represents the minimum elongation required in plastic bag applications, that is, the minimum value of elongation; S max Represents the highest acceptable elongation in plastic bag applications, i.e. the maximum elongation; Use the reference material comparison table to determine the required light transmittance according to the purpose of different plastic bags, and record it as L actual , and according to the maximum light transmittance required in the plastic bag application, the transparency score is calculated by ratio, and the calculation formula is expressed as: Among them: F transparency represents transparency rating; L actual Represents the actual measured light transmittance; L max Represents the highest light transmittance required in this plastic bag application.

3. The plastic bag production monitoring system based on the Internet of Things according to claim 2 is characterized in that: By changing the proportion of plasticizers in the additives, the flexibility and transparency of the plastic bag can be adjusted. The flexibility score and transparency score are used to calculate the proportion of plasticizers in the plastic bag additives. The formula is expressed as: plasticizer =w1·F flexibility +w2·(1-F transparency ), where: w1 and w2 are weight coefficients of flexibility score and transparency score, and w1+w2=1, F flexibility Score flexibility, F transparency Rate transparency.

4. The plastic bag production monitoring system based on the Internet of Things according to claim 3 is characterized in that ； Use the reference material comparison table to determine the required cutting accuracy according to the purpose of different plastic bags; After receiving the ratio of the plasticizer in the plastic bag additives and the cutting accuracy, the process selection module defines the ratio of the plasticizer in the plastic bag additives and the cutting accuracy as input variables, and divides them into different fuzzy sets respectively; The order of punching and cutting bags in the next step of the plastic bag process is defined as the output variable and divided into fuzzy sets; Formulate fuzzy rules to describe the influence of the proportion of plasticizer in plastic bag additives and the definition of cutting accuracy on the order of punching and cutting bags in the next step of the plastic bag process; Perform fuzzy reasoning based on fuzzy rules to determine the order of punching and cutting bags in the next step of the plastic bag production process; Among them, the fuzzy set division method of cutting accuracy is as follows: access the historical database to obtain the cutting accuracy of multiple plastic bag production machines and merge them into a cutting accuracy data set. According to the cutting accuracy data set, the cutting accuracy threshold is set using the percentile method. The data in the cutting accuracy data set is arranged from small to large, and N1% and N2% are set as the percentile ratios, where N1%>N2%.

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