Cost-combined automatic matching design method and system for paper packaging

Abstract

The invention relates to a cost-combined paper product package automatic matching design method and system, and the method comprises the steps: presetting a packaging scheme database, obtaining the attribute of a to-be-packaged target content and an outer package printing parameter, and obtaining a matched packaging design scheme and a printing design scheme; obtaining the product dead weight of the target content and the production plan of the target batch where the target content is located, and calculating the expected deformation rate and the expected fading rate of the target batch in the inventory process; and optimizing the packaging design scheme and the printing design scheme by taking reduction of the expected deformation rate and the expected color fading rate as a target, and selecting alternative optimization schemes meeting optimization conditions to replace the packaging design scheme and the printing design scheme. The system is used for executing the method. According to the method, the production plan of the paper product is combined, the loss in the paper product packaging inventory process is fully considered, and the paper product packaging scheme is comprehensively designed and optimized, so that the paper product packaging design scheme is more reasonable and better fits the actual production of packaging enterprises.

Description

Technical Field

[0001] The present application relates to the technical field of paper packaging design, and in particular to a method and system for automatic matching design of paper packaging in combination with cost. Background Art

[0002] Paper packaging design refers to the process by which packaging companies design paper packaging solutions and carry out packaging processing based on the packaging contents and customer needs. Paper packaging design mainly includes the selection of cardboard type, cardboard thickness and packaging box size. It also includes the printing design on the outer surface of the packaging box, which usually includes the selected ink type and printing process.

[0003] Traditional paper packaging design is mostly done manually based on experience, which is highly dependent on manual experience. With the development of information technology, some packaging design methods based on design models exist in the existing technology. For example, CN113255022A discloses a corrugated paper structure design method and system based on a demand import model. It obtains point cloud data of the product to be packaged, and then obtains the voxel model and placement posture of the product, and then obtains the matching lining model and packaging box model respectively, thereby realizing the automated design of paper packaging.

[0004] This paper packaging automation design method mainly focuses on the structure, size and placement of the product, and does not fully consider the cost of paper packaging design. In particular, in the actual operation of packaging companies, due to the large batch volume of packaged products, the cost of paper packaging is also one of the key issues that packaging companies focus on. More importantly, due to the batch characteristics of paper packaging, when the number of products in a single batch is large or the delivery cycle is long, the packaged paper products need to be temporarily stored in the warehouse for a long period of time. In order to reduce inventory costs, most paper packaging products are stored in stacking. In the actual production process, it is found that when the storage cycle is long, the paper packaging products may experience carton deformation or fading of the outer packaging printing during storage, which will increase the product loss and cost of the packaging company. The paper packaging design method in the existing technology rarely considers the storage loss during the inventory process, which makes the paper packaging design method have certain limitations and needs to be improved. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, this application aims to provide a cost-effective automatic matching design method and system for paper packaging. This application integrates paper product production planning, fully considers the loss of paper packaging during inventory, and comprehensively designs and optimizes paper packaging solutions, making them more reasonable and more in line with the actual production practices of packaging companies.

[0006] The present application discloses a method for automatically matching and designing paper packaging in consideration of cost, comprising the following steps:

[0007] S01. Preset a packaging solution database, wherein the packaging solution database includes attributes of packaging contents and corresponding packaging design solutions, and the packaging solution database also includes outer packaging printing parameters and corresponding printing design solutions;

[0008] S02. Obtaining properties of target contents to be packaged and outer packaging printing parameters, and searching the packaging solution database based on the properties of the target contents and the outer packaging printing parameters to obtain a packaging design solution that matches the properties of the target contents and a printing design solution that matches the outer packaging printing parameters of the target contents;

[0009] S03. Obtain the product weight of the target contents and the production plan of the target batch to which the target contents belong. Based on the production plan, obtain the inventory cycle, stacking height, and environmental parameters of the inventory environment of the target contents, wherein the environmental parameters include ambient temperature, ambient humidity, and light intensity.

[0010] S04. Obtaining an expected deformation rate of the target batch during storage based on the product weight, storage cycle, stacking height, ambient humidity, and packaging design of the target contents; and obtaining an expected fading rate of the target batch during storage based on the outer packaging printing parameters, printing design, storage cycle, ambient temperature, and light intensity of the target contents;

[0011] S05. Optimizing the packaging design and the printing design with the goal of reducing the expected deformation rate and the expected fading rate, obtaining a plurality of first alternative optimization schemes for the packaging design and a plurality of second alternative optimization schemes for the printing design, selecting a first alternative optimization scheme that satisfies a first optimization condition to replace the packaging design, and selecting a second alternative optimization scheme that satisfies a second optimization condition to replace the printing design;

[0012] The first optimization condition is expressed as:

[0013]

[0014] The second optimization condition is expressed as:

[0015]

[0016] in, represents the additional cost of the first alternative optimization solution compared to the initial packaging design solution, Indicates the deformation loss cost reduced by the first alternative optimization scheme compared with the initial packaging design scheme, Indicates the expected deformation rate of the initial packaging design, represents the expected deformation rate of the first alternative optimization solution, m represents the number of target contents to be packaged, and q represents the cost of a single package;

[0017] represents the increased cost of the second alternative optimization solution compared to the initial printing design solution, The second alternative optimization solution reduces the fading loss cost compared to the initial printing design solution. Indicates the expected fading rate of the initial printed design. represents the expected fading rate of the second alternative optimization solution.

[0018] Preferably, the attributes of the packaging contents include the category and size of the packaging contents, and the packaging design plan includes the type of cardboard, cardboard thickness and packaging box size; the outer packaging printing parameters include the printing area and printing color, and the printing design plan includes the type of ink used and the printing process.

[0019] Preferably, in step S01, in the packaging solution database, the attributes of the packaging contents are represented as (UID i , L max ,W max , H max ), where UID i The unique identifier of the category of the package contents, L max ,W max , H max Respectively represent the maximum length, maximum width and maximum height of the package contents;

[0020] In step S02, the category of the target content is obtained and converted into a corresponding unique identifier, and a matching unique identifier is searched in the packaging solution database to obtain a packaging design solution for the category of the target content;

[0021] Get the maximum length of the target content Maximum width Maximum height The packaging design scheme that meets the size matching condition is selected as the packaging design scheme for the target content. The size matching condition is expressed as:

[0022] and,

[0023]

[0024] Preferably, in step S01, the outer packaging printing parameters are expressed as (S j,hue), where S j Indicates the printing area, hue indicates the main hue of the printing color;

[0025] In step S02, the main hue of the printed color of the target content is obtained and recorded as hue tag , search the package solution database for the hue tag Matching primary hues to obtain a printing design that matches the printing color of the target content;

[0026] The printed area of ​​the target content is obtained and recorded as the target area S tag , search among the printing designs that match the printing color of the target content, and select the one with the printing area closest to the target area S tag The printing design scheme is used as the printing design scheme for the target content. Preferably, in step S04, the product weight, inventory cycle, stacking height, ambient humidity, and packaging design scheme of the target content are input into a deformation rate prediction model to obtain the expected deformation rate of the target batch during the inventory process;

[0027] In step S05, the weight of the target product, inventory cycle, stacking height, ambient humidity and the first alternative optimization solution are input into the deformation rate prediction model to obtain the expected deformation rate of the first alternative optimization solution.

[0028] The construction of the deformation rate prediction model includes the following steps:

[0029] Sa01. Acquire first historical inventory data as first sample data, where the first historical inventory data includes the weight of the package contents, inventory cycle, stacking height, ambient humidity, cardboard type, cardboard thickness, and deformation rate.

[0030] Sa02. Preprocess the first sample data and divide the first sample data into a first training set and a first test set;

[0031] Sa03, constructing a deformation rate prediction model, and training the deformation rate prediction model using the first training set;

[0032] Sa04. Use the first test set to test the deformation rate prediction model until the deformation rate prediction model meets the prediction accuracy requirement, and obtain a trained deformation rate prediction model.

[0033] Preferably, in step S04, the outer packaging printing parameters, printing design plan, inventory cycle, ambient temperature and light intensity of the target content are input into a fading rate prediction model to obtain the expected fading rate of the target batch during the inventory process;

[0034] In step S05, the outer packaging printing parameters of the target content, the second alternative optimization solution, the inventory cycle, the ambient temperature and the light intensity are input into the fading rate prediction model to obtain the expected fading rate of the second alternative optimization solution.

[0035] The construction of the fading rate prediction model includes the following steps:

[0036] Sb01. Acquire second historical inventory data as second sample data, where the second historical inventory data includes the printed area of ​​the package contents, the printed color, the inventory cycle, the ambient temperature and light intensity of the inventory environment, the light resistance level and light protection process level of the printing ink, and the fading rate;

[0037] Sb02. Preprocess the second sample data and divide the second sample data into a second training set and a second test set;

[0038] Sb03, constructing a fading rate prediction model, and training the fading rate prediction model using the second training set;

[0039] Sb04. Use the second test set to test the fading rate prediction model until the fading rate prediction model meets the prediction accuracy requirement, and obtain a trained fading rate prediction model.

[0040] Preferably, in step S05, optimizing the packaging design with the goal of reducing the expected deformation rate includes replacing a cardboard type with a higher compressive strength and / or increasing the thickness of the cardboard;

[0041] With the goal of reducing the expected fading rate, optimizing the printing design solution includes replacing an ink type with a higher light fastness level and / or using a light protection process with better light fastness.

[0042] The present application provides a cost-effective automatic matching design system for paper packaging, comprising:

[0043] A database configuration module, which is used to preset a packaging solution database, wherein the packaging solution database includes attributes of packaging contents and corresponding packaging design solutions, and the packaging solution database also includes outer packaging printing parameters and corresponding printing design solutions;

[0044] a search and matching module, configured to obtain the properties of the target contents to be packaged and the printing parameters of the outer packaging, and search the packaging solution database based on the properties of the target contents and the printing parameters of the outer packaging to obtain a packaging design solution that matches the properties of the target contents and a printing design solution that matches the printing parameters of the outer packaging of the target contents;

[0045] a parameter acquisition module, configured to acquire the weight of the target contents and the production plan of the target batch, and based on the production plan, acquire the inventory cycle, stacking height, and environmental parameters of the inventory environment, including ambient temperature, ambient humidity, and light intensity;

[0046] a calculation module configured to obtain an expected deformation rate of the target batch during the inventory process based on the product weight, inventory cycle, stacking height, ambient humidity, and packaging design of the target contents; and to obtain an expected fading rate of the target batch during the inventory process based on the outer packaging printing parameters, printing design, inventory cycle, ambient temperature, and light intensity of the target contents;

[0047] an optimization module configured to optimize the packaging design and the printing design with the goal of reducing the expected deformation rate and the expected fading rate, obtain a plurality of first alternative optimization schemes for the packaging design and a plurality of second alternative optimization schemes for the printing design, select a first alternative optimization scheme that satisfies a first optimization condition to replace the packaging design, and select a second alternative optimization scheme that satisfies a second optimization condition to replace the printing design;

[0048] The first optimization condition is expressed as:

[0049]

[0050] The second optimization condition is expressed as:

[0051]

[0052] in, represents the additional cost of the first alternative optimization solution compared to the initial packaging design solution, Indicates the deformation loss cost reduced by the first alternative optimization scheme compared with the initial packaging design scheme, Indicates the expected deformation rate of the initial packaging design, represents the expected deformation rate of the first alternative optimization solution, m represents the number of target contents to be packaged, and q represents the cost of a single package;

[0053] represents the increased cost of the second alternative optimization solution compared to the initial printing design solution, The second alternative optimization solution reduces the fading loss cost compared to the initial printing design solution. Indicates the expected fading rate of the initial printed design. represents the expected fading rate of the second alternative optimization solution.

[0054] A computer device of the present application includes a processor and a memory connected by signals, wherein the memory stores at least one instruction or at least one program, and when the at least one instruction or the at least one program is loaded by the processor, executes the above-mentioned automatic matching design method for paper packaging combined with cost.

[0055] The present application provides a computer-readable storage medium having stored thereon at least one instruction or at least one program, which, when loaded by a processor, executes the above-mentioned automatic matching design method for paper packaging combined with cost.

[0056] The advantage of the cost-effective automatic matching design method and system for paper packaging described in the present application is that, by obtaining the production plan of the product batch containing the target content, the present application can obtain the product batch inventory cycle, stacking height, and inventory environment parameters, and combine the initial design scheme and inventory parameters of the paper product to predict the two main losses in the inventory process, namely, the carton deformation rate and the outer packaging fading rate. In this way, the loss of the batch of paper products in the packaging process can be predicted, and the optimization cost required to reduce the loss rate is calculated based on this. It is then compared with the cost increased by the optimization, and the scheme with the optimization cost not greater than the loss cost is selected to optimize the paper packaging design scheme, thereby obtaining a more scientific and reasonable paper packaging design scheme that is close to the actual production of the packaging enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a flowchart of the steps of a cost-effective automatic matching design method for paper packaging described in this application.

[0058] Figure 2 Schematic diagram of the structure of the computer device described in this embodiment.

[0059] Description of reference numerals: 101 - processor, 102 - memory. DETAILED DESCRIPTION

[0060] like Figure 1 As shown, the method for automatically matching and designing paper packaging according to the present application includes the following steps:

[0061] S01. Preset a packaging solution database. The packaging solution database includes properties of packaging contents and corresponding packaging design solutions. The packaging solution database also includes outer packaging printing parameters and corresponding printing design solutions.

[0062] Specifically, the attributes of the packaging contents include the category and size of the packaging contents. Category specifically refers to the classification of packaged products, such as cosmetics, food, household products, etc. Different categories of products are suitable for different packaging solutions. Size specifically refers to the maximum size of the packaging contents, namely the maximum length, maximum width and maximum height. Most packaged products are irregular in shape, so it is necessary to select the maximum size to ensure that the packaging box can wrap the product.

[0063] The properties of the package contents are represented in the packaging solution database as (UID i , L max ,W max , H max ), where UID i The unique identifier of the category of the package contents, L max ,W max , H max Respectively represent the maximum length, maximum width and maximum height of the package contents. For example, the numbers 1, 2 and 3 are used as the unique identifiers of cosmetics, food and household products respectively. The package contents of the cosmetics category with a maximum length of 20cm, a maximum width of 15cm and a maximum height of 10cm are represented as (1, 20, 15, 10) in the packaging solution database. Each package content has a corresponding packaging design solution. The packaging design solution mainly includes the cardboard type, cardboard thickness and packaging box size. The cardboard type, cardboard thickness and packaging box size can be designed according to the standardized parameters of the packaging company. For example, the cardboard type has Corrugated paper, cardboard, grey board, cardboard thickness can be selected as 0.2cm, 0.4cm, etc. Cardboard size can be designed into a variety of standard specifications of rectangular boxes, such as 15cm*8cm*6cm, 25cm*18cm*12cm, etc. Packaging companies can flexibly configure according to their own production reality. Each packaging content has a corresponding suitable packaging design scheme. For example, if the category is cosmetics, the maximum length is 20cm, the maximum width is 15cm, and the maximum height is 10cm, the corresponding corrugated paper, cardboard thickness is 0.2cm, and the packaging box size is 25cm*18cm*12cm.

[0064] Exemplarily, in step S02, the category of the target content is obtained and converted into a corresponding unique identifier, and a matching unique identifier is searched in the packaging solution database to obtain a packaging design solution for the category in which the target content belongs. For example, if the operator inputs that the target content of this packaging is cosmetics, it is converted into a unique identifier 1, and a packaging design solution with a unique identifier of 1 is searched in the packaging database, which is the packaging design solution for the category in which the target content belongs.

[0065] Then get the maximum length of the target content Maximum width Maximum height In this step, the operator can enter the maximum length of the target content Maximum width Maximum height It can also be combined with three-dimensional scanning technology to scan the target content with a three-dimensional scanner to automatically obtain the size information of the target content.

[0066] The packaging design scheme that meets the size matching condition is selected as the packaging design scheme for the target content. The size matching condition is expressed as:

[0067] and,

[0068]

[0069] The above formula indicates that among the packaging contents of the same category, the packaging design scheme whose maximum length, maximum width, and maximum height are all greater than the target contents and closest to the target contents size is selected. The specific screening method is to calculate the difference between the size of each packaging design scheme and the size of the target contents, specifically the difference in maximum length, maximum width, and maximum height. The three differences are then summed to represent the difference in size between the packaging design scheme and the target contents. The packaging design scheme with the smallest sum is the packaging design scheme whose size is closest to the target contents, and this packaging design scheme is selected as the packaging design scheme for the target contents.

[0070] For example, there are four packaging design options for cosmetics, with maximum sizes of 10cm*12cm*8cm, 15cm*8cm*6cm, 25cm*18cm*12cm, and 30cm*22cm*15cm.

[0071] The dimensions of the target contents are a maximum length of 20 cm, a maximum width of 15 cm, and a maximum height of 10 cm. First, the maximum dimensions are compared. The maximum dimensions of Plan 1 and Plan 2 are both smaller than the target contents and do not meet the packaging conditions and are eliminated. Plans 3 and 4 meet the maximum dimension requirements and their maximum dimensions are both larger than the target contents, so further calculations are performed.

[0072] Calculation shows that the sum of the size differences between Scheme 3 and the target content is:

[0073] (25-20)+(18-15)+(12-10)=10.

[0074] The sum of the size differences between Scheme 4 and the target contents is:

[0075] (30-20)+(22-15)+(15-10)=22.

[0076] The sum of the two size differences is numerically compared, and the solution with the smallest sum of size differences is selected as the packaging design solution for the target content, that is, Solution 3.

[0077] The outer packaging printing parameters include printing area and printing color. In the packaging solution database, since most printed patterns are irregular in shape and the printing area is not standardized, they are expressed in the form of range values, for example (5cm 2 ,8cm 2 ). The printing color is represented by the main hue of the printed pattern. The main hue refers to the hue that occupies the largest proportion of the pattern, such as red tones, blue-green series, etc. When performing printing color matching, it is only necessary to match the printing design scheme with a color similar to the target content. For example, if the outer packaging of the target content is mainly red and yellow, then match the printing design scheme that is also mainly red and yellow. The calculation method of the main hue belongs to the existing technology. For example, the main hue is obtained by color statistics, specifically including extracting the RGB value of the printed pattern, compressing the RGB value according to the color scale, such as mapping it to 16 color scales, and establishing a 64MB hash table to count the frequency of occurrence of each color, and selecting the color with the highest frequency of occurrence as the main hue of the pattern. Taking the 12-hue ring as an example, 30° represents orange-yellow and 60° represents orange. In this step, the main color of the printed pattern is represented by the main hue of the printed pattern.

[0078] The printing design plan includes the type of ink and printing process used. In actual production, the size of the printing area and the main color will affect the type of ink and printing process used. Packaging companies can configure according to the type of ink and process used in actual production. For example, ink types include polyamide inks, composite inks, UV inks, water-based inks, etc., and printing processes include offset lithography, flexographic offset printing, gravure printing, screen printing, etc. Based on production experience, appropriate ink types and printing processes are configured for packaging products with different printing areas and printing colors. In addition, the printing process also includes whether a light protection process is used. The light protection process can be graded according to the light protection effect. For example, the first-level light protection process is a water-based varnish process, and the second-level light protection process is a lamination or UV varnish process. In this step, the outer packaging printing parameters are expressed as the printing area range and the main color phase, and the printing design plan is expressed as the type of ink and printing process used.

[0079] In step S02, when matching the printing design, the main hue of the printing color of the target content is obtained and recorded as hue tagSpecifically, the main hue of the printed sample can be obtained by obtaining an image of the printed sample through the above-mentioned image color statistics method. The main hue is the main hue of the target content, which is used to represent the main color of the printed pattern on the outer packaging of the target content.

[0080] Search the packaging solution database for the primary hue that matches the printed color of the target content. tag Matching primary hues to obtain a printing design that matches the printing color of the target content.

[0081] For example, in the packaging solution database, there are 12 main hue printing design solutions classified by the 12-color wheel, namely 0° / 360° yellow, 30° orange-yellow, ... 330° yellow-green, representing 12 main color printing design solutions respectively.

[0082] When matching printing design plans, the main hue of the target content's outer packaging printing pattern is first obtained, and then the absolute value is taken after subtracting it from the 12 main hues. The one with the smallest absolute value of the difference is taken as the printing design plan with the main color closest to the target content's outer packaging printing pattern.

[0083] After matching the main color, different printing processes will be used for printed patterns of different printing areas. For example, for printed patterns of small areas, flexographic printing is suitable, and for printed patterns of medium areas, lithographic offset printing or screen printing is suitable. Therefore, in this step, after matching the main color, further matching is performed according to the printing area of ​​the printed pattern on the outer packaging of the target content.

[0084] Specifically, as mentioned above, the printing area in the printing design is expressed in the form of a range value. First, the printing area of ​​the target content is obtained and recorded as the target area S. tag The area of ​​the printed pattern can be extracted by image recognition algorithm, or the operator can measure and input the target area S tag , search among several printing design schemes with matching main colors and select the one with the printing area closest to the target area S tag The printing design scheme of the target content is as the printing design scheme of the target content, and the specific selection rule is the target area S tag Located within the area of ​​the printing design.

[0085] For example, by obtaining the main hue of the target content's outer packaging printing, for example, orange-yellow with a main hue of 30°, searching among the printing design schemes, obtaining several printing design schemes with a main hue of 30°, and then obtaining the printing area of ​​the target content's outer packaging printing, searching among several printing design schemes with a main hue of 30°, obtaining a printing design scheme with a matching printing area, which is the printing design scheme corresponding to the target content.

[0086] In the previous steps, we selected packaging and printing designs that matched the target content. In this step, we will optimize the packaging and printing designs based on inventory loss. The specific steps are as follows:

[0087] The applicant found in actual production that for paper packaging with large quantities or long inventory cycles, the main losses of the packaged products during the inventory process are deformation and fading. Due to storage cost considerations, paper packaging is mostly stored in stacks, and it is difficult to avoid sunlight. The stacking method will cause paper packaging products to collapse and other deformation losses, while sunlight exposure will cause printed patterns to fade. The applicant analyzed the causes of these two loss phenomena, obtained the main factors affecting the deformation and fading of cartons, and based on these factors, predicted the expected deformation rate and expected fading rate of paper packaging during the inventory process.

[0088] Specifically:

[0089] First, it is necessary to screen out the factors that affect the deformation of the packaging, including the weight of the target content, inventory cycle, stacking height, ambient humidity and packaging design.

[0090] The weight of the target product is the main source of weight for the packaged product. The heavier the product, the greater the overall weight after packaging, and the more likely the lower packaging will be deformed during stacking.

[0091] Both inventory cycle and stacking height are positively correlated with deformation. The longer the inventory cycle, the higher the probability of deformation of paper packaging products. The higher the stacking height, the greater the load on the packaging on the lower layer, making it more susceptible to deformation.

[0092] Ambient humidity is positively correlated with the expected deformation rate of paper packaging products. The higher the ambient humidity, the higher the probability of cardboard softening and deformation. For example, some studies have shown that for every 10% increase in ambient humidity, the compressive strength of cardboard will decrease by 0.8% to 1.2%, resulting in an increase in deformation rate.

[0093] It is easy to understand that the compressive strength and thickness of the cardboard in the packaging design are negatively correlated with the probability of deformation. The higher the compressive strength of the cardboard and the thicker the cardboard, the lower the probability of deformation.

[0094] In the above steps, various factors that may affect the deformation rate during the inventory process of packaged products are screened out, and based on these factors, the deformation rate of a batch of packaged products during the inventory cycle is predicted. In this embodiment, the prediction is performed using machine learning, which specifically includes the following steps:

[0095] Inputting the product weight, inventory cycle, stacking height, ambient humidity, and packaging design of the target content into a deformation rate prediction model to obtain the expected deformation rate of the target batch during the inventory process;

[0096] In step S05, the weight of the target product, inventory cycle, stacking height, ambient humidity and the first alternative optimization solution are input into the deformation rate prediction model to obtain the expected deformation rate of the first alternative optimization solution.

[0097] Among them, the inventory cycle can be obtained based on the company's production and delivery plan, the stacking height is obtained based on the total volume of the batch of products and the available stacking area, and the ambient humidity is taken as the average humidity of the inventory environment 7 days before the current moment, or the inventory environment humidity during the same period in history.

[0098] The construction of the deformation rate prediction model includes the following steps:

[0099] Sa01. Acquire first historical inventory data as first sample data, where the first historical inventory data includes the weight of the package contents, inventory cycle, stacking height, ambient humidity, cardboard type, cardboard thickness, and deformation rate.

[0100] Sa02. Preprocess the first sample data and divide the first sample data into a first training set and a first test set;

[0101] Sa03, constructing a deformation rate prediction model, and training the deformation rate prediction model using the first training set;

[0102] Sa04. Use the first test set to test the deformation rate prediction model until the deformation rate prediction model meets the prediction accuracy requirement, and obtain a trained deformation rate prediction model.

[0103] Exemplarily, historical inventory data of the inventory area is collected as first sample data. The first historical data includes the weight of the product in the package, inventory cycle, stacking height, ambient humidity, cardboard type, cardboard thickness and deformation rate. Among them, the stacking height is the maximum stacking height, the ambient humidity is the average ambient humidity within the inventory cycle, and the deformation rate is obtained by dividing the number of deformed packages by the total number of packages.

[0104] For example, collecting 500 sets of first sample data is as follows:

[0105]

[0106] After obtaining the first sample data as mentioned above, the data is preprocessed, including data cleaning and removal of outliers, and then the data is normalized using the Z-score standardization method.

[0107] The first sample data is divided into, for example, 80% as a training set and 20% as a test set.

[0108] A neural network was chosen as the deformation rate prediction model. Six neurons were designed in the input layer, corresponding to six related factors: product weight, inventory cycle, stacking height, ambient humidity, cardboard type, and cardboard thickness. One neuron was set in the output layer, corresponding to the deformation rate output.

[0109] In an optional embodiment, the prediction accuracy of the model can be improved by setting a hidden layer and an attention layer. For example, a hidden layer can be set to analyze the effect of humidity on cardboard creep, that is, the relationship between humidity and the compressive strength of cardboard.

[0110] The lambda layer is used to limit the range of the predicted deformation rate, huberloss is used as the loss function, AdanW is selected as the model optimizer, the initial learning rate is set to 0.001, the batch size is 64, and the early stopping mechanism is introduced to prevent the model from overfitting. This completes the preliminary configuration of the model.

[0111] The model is trained using data from the training set to establish a mapping between various correlation factors and deformation rates. After a certain number of training cycles, the model's accuracy is tested using data from the test set until the model meets the prediction accuracy requirements. This results in the deformation rate prediction model. This model can predict the deformation rate of a batch of packaging products during the inventory cycle based on the input parameters of the packaging contents, product weight, inventory cycle, stacking height, ambient humidity, cardboard type, and cardboard thickness.

[0112] In step S04, it can be used to predict the deformation rate of the initial packaging design solution, and in step S05, it can be used to predict the deformation rate of the first alternative optimization solution.

[0113] In other optional embodiments, those skilled in the art may select other machine learning models according to actual needs, such as a random forest model, an XGBoost model, etc., and this embodiment is not limited to this.

[0114] Through this step, the deformation rate of the packaged product can be predicted by combining various associated factors related to the deformation of the packaged product.

[0115] In step S04, the outer packaging printing parameters, printing design plan, inventory cycle, ambient temperature and light intensity of the target content are input into a fading rate prediction model to obtain the expected fading rate of the target batch during the inventory process;

[0116] In step S05, the outer packaging printing parameters of the target content, the second alternative optimization solution, the inventory cycle, the ambient temperature and the light intensity are input into the fading rate prediction model to obtain the expected fading rate of the second alternative optimization solution.

[0117] Among them, the inventory cycle can be obtained based on the company's production and delivery plan, and the ambient temperature and light intensity can be taken as the average value of the inventory environment 7 days before the current moment, or the historical value for the same period can be taken.

[0118] The construction of the fading rate prediction model includes the following steps:

[0119] Sb01. Acquire second historical inventory data as second sample data, where the second historical inventory data includes the printed area of ​​the package contents, the printed color, the inventory cycle, the ambient temperature and light intensity of the inventory environment, the light resistance level and light protection process level of the printing ink, and the fading rate;

[0120] Sb02. Preprocess the second sample data and divide the second sample data into a second training set and a second test set;

[0121] Sb03, constructing a fading rate prediction model, and training the fading rate prediction model using the second training set;

[0122] Sb04. Use the second test set to test the fading rate prediction model until the fading rate prediction model meets the prediction accuracy requirement, and obtain a trained fading rate prediction model.

[0123] Similarly, in this step, a variety of factors that may affect packaging fading are screened out, specifically the outer packaging printing parameters, printing design plan, inventory cycle, ambient temperature and light intensity of the target content, and the expected fading rate of the target batch during the inventory process is calculated.

[0124] The outer packaging printing parameters include printing area and printing color, and the printing design plan includes the type of ink and printing process used.

[0125] The print area is positively correlated with the expected fading rate; the larger the print area, the higher the likelihood of fading.

[0126] Different colors have varying sensitivities to UV rays and varying probabilities of fading due to light. Generally speaking, colors with a hue angle of 0° to 60° are most sensitive to UV rays and are most susceptible to discoloration due to light exposure. Colors with a hue angle of 60° to 180° are second most sensitive, while other colors are less sensitive to UV rays. The primary hue of the printed pattern is used to represent the printed color. The method for obtaining the primary hue can be understood by referring to the description above and will not be elaborated on here.

[0127] As inventory cycles increase, the risk of printed patterns fading increases. In an exemplary scenario, the fading rate increases by 2% for every 30 days the inventory cycle increases.

[0128] Ambient temperature increases significantly affect the photooxidation rate of ink, thereby increasing the fading rate. Ambient temperature is generally positively correlated with the probability of ink fading. The average temperature over a certain period, such as 7 days, is used as the ambient temperature.

[0129] The stronger the light intensity, the more likely the printed color will fade and the higher the fading rate. The average light intensity in a certain period of the inventory environment, for example, 7 days, is taken as the light intensity value.

[0130] Different types of printing inks have different light fastness levels. In this step, different types of printing inks are classified according to their light fastness levels.

[0131] It is easy to understand that the higher the level of light protection process used, the less likely the printed pattern will fade. Therefore, in this embodiment, the printing process is classified according to whether a light protection process is used and the level of light protection process used. In a feasible embodiment, it can be classified into no light protection process, first-level light protection process and second-level light protection process, among which the first-level light protection level is the water-based varnish process, and the second-level light protection process is the lamination or UV varnishing process.

[0132] The fading rate is calculated by counting the number of packages that fade in a batch and dividing it by the total number of packages in the batch.

[0133] Exemplarily, 500 sets of second sample data are collected as follows:

[0134]

[0135] After obtaining the second sample data as mentioned above, the data is preprocessed, including data cleaning and removal of outliers, and then the data is normalized using the Z-score standardization method.

[0136] The second sample data is divided into, for example, 80% as a training set and 20% as a test set.

[0137] It is preferred to use the same machine learning model as the aforementioned deformation rate prediction model as the fading rate prediction model to facilitate unified deployment of the model.

[0138] Taking the neural network as an example of a fading rate prediction model, the input layer is set with 7 neurons, corresponding to the printing area, the main hue angle of the printed color, the inventory cycle, the ambient temperature, the light intensity, the light resistance level, and the light protection level. The output layer is set with 1 neuron, corresponding to the fading rate.

[0139] The lambda layer is used to limit the range of the predicted fading rate, huberloss is used as the loss function, AdanW is selected as the model optimizer, the initial learning rate is set to 0.001, the batch size is 64, and the early stopping mechanism is introduced to prevent the model from overfitting. This completes the preliminary configuration of the model.

[0140] The model is trained using data from the training set to establish a mapping between various associated factors and fading rates. After a certain number of training cycles, the model's accuracy is tested using data from the test set until the model meets the prediction accuracy requirements, thereby obtaining the fading rate prediction model. This model can predict the fading rate of a batch of packaged products during the inventory cycle based on the input parameters of the printed area of ​​the packaging contents, the primary hue angle of the printed color, the inventory cycle, the ambient temperature, the light intensity, the light resistance level, and the light protection level.

[0141] In step S04, it can be used to predict the fading rate of the initial printing design solution, and in step S05, it can be used to predict the fading rate of the second alternative optimization solution.

[0142] In other optional embodiments, those skilled in the art may select other machine learning models according to actual needs, such as a random forest model, an XGBoost model, etc., and this embodiment is not limited to this.

[0143] Through this step, the fading rate of the packaged product can be predicted by combining various associated factors related to the fading of the packaged product.

[0144] Optimizing the packaging design and the printing design with the goal of reducing the expected deformation rate and the expected fading rate to obtain several first alternative optimization schemes for the packaging design and several second alternative optimization schemes for the printing design, selecting the first alternative optimization scheme that meets the first optimization condition to replace the packaging design, and selecting the second alternative optimization scheme that meets the second optimization condition to replace the printing design;

[0145] The first optimization condition is expressed as:

[0146]

[0147] The second optimization condition is expressed as:

[0148]

[0149]

[0150] in, represents the additional cost of the first alternative optimization solution compared to the initial packaging design solution, Indicates the deformation loss cost reduced by the first alternative optimization scheme compared with the initial packaging design scheme, Indicates the expected deformation rate of the initial packaging design, represents the expected deformation rate of the first alternative optimization solution, m represents the number of target contents to be packaged, and q represents the cost of a single package;

[0151] represents the increased cost of the second alternative optimization solution compared to the initial printing design solution, The second alternative optimization solution reduces the fading loss cost compared to the initial printing design solution. Indicates the expected fading rate of the initial printed design. represents the expected fading rate of the second alternative optimization solution.

[0152] With the goal of reducing the expected deformation rate, optimizing the packaging design solution includes replacing the type of cardboard with higher compressive strength and / or increasing the thickness of the cardboard. Specifically, the cardboard types are graded according to compressive strength. For example, the compressive strength of all available cardboards are listed and arranged from small to large, and then divided into several equal intervals, each interval representing a compressive strength grade, and a higher grade indicates a higher compressive strength.

[0153] Similarly, the thickness of the available cardboard is arranged from small to large and divided into several intervals. Each interval represents a thickness level, and the higher the level, the thicker the thickness.

[0154] Optimizing the packaging design with the goal of reducing deformation can specifically include replacing the cardboard type in the packaging design with one with a higher compressive strength rating and / or replacing the cardboard thickness with a higher thickness rating. For example, there are five levels of compressive strength and thickness for different types of cardboard. The initial packaging design has a compressive strength rating of 2 and a thickness rating of 3. When optimizing the packaging design, either compressive strength or thickness can be optimized separately, or both can be optimized simultaneously. For example, the following first alternative optimization solution can be proposed:

[0155] Option 1: Replace the cardboard type with a compressive strength level of 3, while keeping the cardboard thickness unchanged.

[0156] Option 2: The compressive strength level remains unchanged, and the cardboard thickness level is changed to level 4.

[0157] Option 3: Replace the cardboard type with a compressive strength level of 4, while keeping the cardboard thickness unchanged.

[0158] Option 4: The compressive strength grade remains unchanged, and the cardboard thickness grade is changed to grade 5.

[0159] Option 5: Replace the cardboard type with a compressive strength of level 3 and the cardboard thickness grade of level 4.

[0160] This yields multiple alternative optimization solutions. Based on the first optimization condition, the solution with the increased cost less than or equal to the reduced deformation loss cost is selected as the candidate optimization solution. The idea behind this step is that if the increased cost is greater than the reduced deformation loss cost, the optimization solution is not practical, and reprocessing the original solution to replace the packaging lost due to deformation is more effective for the company.

[0161] It is easy to understand that when multiple alternatives all meet the first optimization condition above, the and Make a difference and take the group with the largest difference as the final optimization solution to replace the initial packaging design solution.

[0162] With the goal of reducing the expected fading rate, optimizing the printing design solution includes replacing an ink type with a higher light fastness level and / or using a light protection process with better light fastness.

[0163] Specifically, the ink types have universal light resistance grade classifications, and the existing light resistance grade classifications can be directly adopted. The light protection process level is set to no protection process, the first-level light protection level is water-based varnish process, and the second-level light protection process is lamination or UV varnish process.

[0164] For example, in the initial printing design, the ink light resistance level is level 2, and there is no light protection process, so there is the following second alternative optimization solution:

[0165] Option 1: The ink light resistance level is level 2, and the first-level light protection process is adopted.

[0166] Option 2: The ink light resistance level is level 2, and the secondary light protection process is adopted.

[0167] Option 3: The ink light resistance level is level 3, without light protection process.

[0168] Option 4: The ink light resistance level is 4, without light protection process.

[0169] Option 5: The ink light resistance level is level 3, and the first-level light protection process is adopted.

[0170] Thus, multiple alternative optimization schemes can be obtained, and then according to the above second optimization condition, the schemes whose cost increase is less than or equal to the cost of fading loss are selected as optional optimization schemes. Similarly, when there are multiple alternative schemes that meet the above second optimization condition, the and Make a difference and take the group with the largest difference as the final optimization solution to replace the initial printing design solution.

[0171] By obtaining the production plan of the product batch containing the target content, this application can obtain the product batch inventory cycle, stacking height, and inventory environment parameters, etc., and combine the initial design plan and inventory parameters of the paper product to predict the two main losses in the inventory process, namely the carton deformation rate and the outer packaging fading rate. In this way, the loss of this batch of paper products in the packaging process can be predicted, and the optimization cost required to reduce the loss rate is calculated based on this. It is then compared with the cost increased by the optimization, and the solution with the optimization cost not greater than the loss cost is selected to optimize the paper packaging design solution. In this way, a more scientific and reasonable paper packaging design solution that is close to the actual production of packaging companies can be obtained.

[0172] This embodiment also provides a cost-effective automatic matching design system for paper packaging, including:

[0173] A database configuration module, which is used to preset a packaging solution database, wherein the packaging solution database includes attributes of packaging contents and corresponding packaging design solutions, and the packaging solution database also includes outer packaging printing parameters and corresponding printing design solutions;

[0174] a search and matching module, configured to obtain the properties of the target contents to be packaged and the printing parameters of the outer packaging, and search the packaging solution database based on the properties of the target contents and the printing parameters of the outer packaging to obtain a packaging design solution that matches the properties of the target contents and a printing design solution that matches the printing parameters of the outer packaging of the target contents;

[0175] a parameter acquisition module, configured to acquire the weight of the target contents and the production plan of the target batch, and based on the production plan, acquire the inventory cycle, stacking height, and environmental parameters of the inventory environment, including ambient temperature, ambient humidity, and light intensity;

[0176] a calculation module configured to obtain an expected deformation rate of the target batch during the inventory process based on the product weight, inventory cycle, stacking height, ambient humidity, and packaging design of the target contents; and to obtain an expected fading rate of the target batch during the inventory process based on the outer packaging printing parameters, printing design, inventory cycle, ambient temperature, and light intensity of the target contents;

[0177] an optimization module configured to optimize the packaging design and the printing design with the goal of reducing the expected deformation rate and the expected fading rate, obtain a plurality of first alternative optimization schemes for the packaging design and a plurality of second alternative optimization schemes for the printing design, select a first alternative optimization scheme that satisfies a first optimization condition to replace the packaging design, and select a second alternative optimization scheme that satisfies a second optimization condition to replace the printing design;

[0178] The first optimization condition is expressed as:

[0179]

[0180] The second optimization condition is expressed as:

[0181]

[0182]

[0183] in, represents the additional cost of the first alternative optimization solution compared to the initial packaging design solution, Indicates the deformation loss cost reduced by the first alternative optimization scheme compared with the initial packaging design scheme, Indicates the expected deformation rate of the initial packaging design, represents the expected deformation rate of the first alternative optimization solution, m represents the number of target contents to be packaged, and q represents the cost of a single package;

[0184] represents the increased cost of the second alternative optimization solution compared to the initial printing design solution, The second alternative optimization solution reduces the fading loss cost compared to the initial printing design solution. Indicates the expected fading rate of the initial printed design. represents the expected fading rate of the second alternative optimization solution.

[0185] The system of this embodiment and the above-mentioned method belong to the same inventive concept, which can be understood with reference to the above description and will not be repeated here.

[0186] like Figure 2As shown, this embodiment also provides a computer device, including a processor 101 and a memory 102 connected via bus signals. The memory 102 stores at least one instruction or at least one program segment, which, when loaded by the processor 101, executes the method described above. The memory 102 can be used to store software programs and modules. The processor 101 executes various functional applications by running the software programs and modules stored in the memory 102. The memory 102 may primarily include a program storage area and a data storage area. The program storage area may store an operating system, application programs required for functions, etc.; the data storage area may store data generated based on the use of the device, etc. In addition, the memory 102 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 102 may also include a memory controller to provide the processor 101 with access to the memory 102.

[0187] The method embodiments provided in the embodiments of the present application can be executed in a computer terminal, server, or similar computing device. That is, the computer device may include a computer terminal, server, or similar computing device. The internal structure of the computer device may include, but is not limited to, a processor, a network interface, and a memory. The processor, network interface, and memory within the computer device may be connected via a bus or other means.

[0188] The processor 101 (also known as the CPU (Central Processing Unit)) is the computing and control core of the computer device. The network interface may optionally include a standard wired interface or a wireless interface (such as Wi-Fi, mobile communication interface, etc.). Memory 102 (Memory) is a memory device in the computer device used to store programs and data. It is understood that the memory 102 here can be a high-speed RAM storage device or a non-volatile memory device (such as at least one disk storage device); optionally, it can also be at least one storage device located remote from the processor 101. Memory 102 provides storage space that stores the operating system of the electronic device, which may include but is not limited to: Windows system (an operating system), Linux (an operating system), Android (a mobile operating system) system, iOS (a mobile operating system), etc., which are not limited in this application. In addition, the storage space also stores one or more instructions suitable for being loaded and executed by the processor 101. These instructions may be one or more computer programs (including program code). In the embodiment of this specification, the processor 101 loads and executes one or more instructions stored in the memory 102 to implement the method described in the above method embodiment.

[0189] The present application also provides a computer-readable storage medium having at least one instruction or at least one program stored thereon, which executes the method described above when loaded by the processor 101. The computer-readable storage medium carries one or more programs, and when the one or more programs are executed, the method according to the present application is implemented.

[0190] According to an embodiment of the present application, a computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0191] In the description of this application, it should be understood that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "horizontal, vertical, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the scope of protection of this application.

[0192] Those skilled in the art can make various other corresponding changes and deformations based on the technical solutions and concepts described above, and all of these changes and deformations should fall within the scope of protection of the claims of this application.

Claims

1. A cost-effective automatic matching design method for paper packaging, characterized in that: The following steps are involved: S01. Preset a packaging solution database, wherein the packaging solution database includes attributes of packaging contents and corresponding packaging design solutions, and the packaging solution database also includes outer packaging printing parameters and corresponding printing design solutions; S02. Obtaining properties of target contents to be packaged and outer packaging printing parameters, and searching the packaging solution database based on the properties of the target contents and the outer packaging printing parameters to obtain a packaging design solution that matches the properties of the target contents and a printing design solution that matches the outer packaging printing parameters of the target contents; S03. Obtain the product weight of the target contents and the production plan of the target batch to which the target contents belong. Based on the production plan, obtain the inventory cycle, stacking height, and environmental parameters of the inventory environment of the target contents, wherein the environmental parameters include ambient temperature, ambient humidity, and light intensity. S04. Obtaining an expected deformation rate of the target batch during the inventory process based on the product weight, inventory cycle, stacking height, ambient humidity, and packaging design of the target contents; Obtaining an expected fading rate of the target batch during storage based on the outer packaging printing parameters, printing design plan, storage cycle, ambient temperature, and light intensity of the target content; S05. Optimizing the packaging design and the printing design with the goal of reducing the expected deformation rate and the expected fading rate, obtaining a plurality of first alternative optimization schemes for the packaging design and a plurality of second alternative optimization schemes for the printing design, selecting a first alternative optimization scheme that satisfies a first optimization condition to replace the packaging design, and selecting a second alternative optimization scheme that satisfies a second optimization condition to replace the printing design; The first optimization condition is expressed as: The second optimization condition is expressed as: in, represents the additional cost of the first alternative optimization solution compared to the initial packaging design solution, Indicates the deformation loss cost reduced by the first alternative optimization scheme compared with the initial packaging design scheme, Indicates the expected deformation rate of the initial packaging design, represents the expected deformation rate of the first alternative optimization solution, m represents the number of target contents to be packaged, and q represents the cost of a single package; represents the increased cost of the second alternative optimization solution compared to the initial printing design solution, The second alternative optimization solution reduces the fading loss cost compared to the initial printing design solution. Indicates the expected fading rate of the initial printed design. represents the expected fading rate of the second alternative optimization solution.

2. The method for automatically matching and designing paper packaging according to claim 1, characterized in that: The attributes of the packaging contents include the category and size of the packaging contents, and the packaging design plan includes the type of cardboard, cardboard thickness and packaging box size; the outer packaging printing parameters include the printing area and printing color, and the printing design plan includes the type of ink used and the printing process.

3. The method for automatic matching design of paper packaging combined with cost according to claim 2, characterized in that: Step S01: In the packaging solution database, the attributes of the packaging contents are represented as (UID i , L max ,W max , H max ), where UID i The unique identifier of the category of the package contents, L max , W max , H max Respectively represent the maximum length, maximum width and maximum height of the package contents; In step S02, the category of the target content is obtained and converted into a corresponding unique identifier, and a matching unique identifier is searched in the packaging solution database to obtain a packaging design solution for the category of the target content; Get the maximum length of the target content Maximum width Maximum height The packaging design scheme that meets the size matching condition is selected as the packaging design scheme for the target content. The size matching condition is expressed as: and, 4. The method for automatically matching and designing paper packaging according to claim 2, characterized in that: In step S01, the outer packaging printing parameters are expressed as (S j ,hue), where S j Indicates the printing area, hue indicates the main hue of the printing color; In step S02, the main hue of the printed color of the target content is obtained and recorded as hue tag , search the package solution database for the hue tag Matching primary hues to obtain a printing design that matches the printing color of the target content; The printed area of ​​the target content is obtained and recorded as the target area S tag , search among the printing designs that match the printing color of the target content, and select the one with the printing area closest to the target area S tag The printing design scheme is used as the printing design scheme of the target content.

5. The method for automatic matching design of paper packaging combined with cost according to claim 2, characterized in that: In step S04, the weight of the target product, inventory cycle, stacking height, ambient humidity and packaging design are input into the deformation rate prediction model to obtain the expected deformation rate of the target batch during the inventory process. In step S05, the weight of the target product, inventory cycle, stacking height, ambient humidity and the first alternative optimization solution are input into the deformation rate prediction model to obtain the expected deformation rate of the first alternative optimization solution. The construction of the deformation rate prediction model includes the following steps: Sa01. Acquire first historical inventory data as first sample data, where the first historical inventory data includes the weight of the package contents, inventory cycle, stacking height, ambient humidity, cardboard type, cardboard thickness, and deformation rate. Sa02. Preprocess the first sample data and divide the first sample data into a first training set and a first test set; Sa03, constructing a deformation rate prediction model, and training the deformation rate prediction model using the first training set; Sa04. Use the first test set to test the deformation rate prediction model until the deformation rate prediction model meets the prediction accuracy requirement, and obtain a trained deformation rate prediction model.

6. The method for automatically matching and designing paper packaging according to claim 2, characterized in that: In step S04, the outer packaging printing parameters, printing design, inventory cycle, ambient temperature and light intensity of the target content are input into the fading rate prediction model to obtain the expected fading rate of the target batch during the inventory process. In step S05, the outer packaging printing parameters of the target content, the second alternative optimization solution, the inventory cycle, the ambient temperature and the light intensity are input into the fading rate prediction model to obtain the expected fading rate of the second alternative optimization solution. The construction of the fading rate prediction model includes the following steps: Sb01. Acquire second historical inventory data as second sample data, where the second historical inventory data includes the printed area of ​​the package contents, the printed color, the inventory cycle, the ambient temperature and light intensity of the inventory environment, the light resistance level and light protection process level of the printing ink, and the fading rate; Sb02. Preprocess the second sample data and divide the second sample data into a second training set and a second test set; Sb03, constructing a fading rate prediction model, and training the fading rate prediction model using the second training set; Sb04. Use the second test set to test the fading rate prediction model until the fading rate prediction model meets the prediction accuracy requirement, and obtain a trained fading rate prediction model.

7. The method for automatically matching and designing paper packaging according to claim 2, characterized in that: In step S05, with the goal of reducing the expected deformation rate, the packaging design solution is optimized, including replacing a cardboard type with a higher compressive strength and / or increasing the thickness of the cardboard; With the goal of reducing the expected fading rate, optimizing the printing design solution includes replacing an ink type with a higher light fastness level and / or using a light protection process with better light fastness.

8. A cost-effective paper packaging automatic matching design system, characterized by: include: A database configuration module, which is used to preset a packaging solution database, wherein the packaging solution database includes attributes of packaging contents and corresponding packaging design solutions, and the packaging solution database also includes outer packaging printing parameters and corresponding printing design solutions; a search and matching module, configured to obtain the properties of the target contents to be packaged and the printing parameters of the outer packaging, and search the packaging solution database based on the properties of the target contents and the printing parameters of the outer packaging to obtain a packaging design solution that matches the properties of the target contents and a printing design solution that matches the printing parameters of the outer packaging of the target contents; a parameter acquisition module, configured to acquire the weight of the target contents and the production plan of the target batch, and based on the production plan, acquire the inventory cycle, stacking height, and environmental parameters of the inventory environment, including ambient temperature, ambient humidity, and light intensity; a calculation module for obtaining an expected deformation rate of the target batch during the inventory process based on the product weight, inventory cycle, stacking height, ambient humidity, and packaging design of the target contents; Obtaining an expected fading rate of the target batch during storage based on the outer packaging printing parameters, printing design plan, storage cycle, ambient temperature, and light intensity of the target content; an optimization module configured to optimize the packaging design and the printing design with the goal of reducing the expected deformation rate and the expected fading rate, obtain a plurality of first alternative optimization schemes for the packaging design and a plurality of second alternative optimization schemes for the printing design, select a first alternative optimization scheme that satisfies a first optimization condition to replace the packaging design, and select a second alternative optimization scheme that satisfies a second optimization condition to replace the printing design; The first optimization condition is expressed as: The second optimization condition is expressed as: in, represents the additional cost of the first alternative optimization solution compared to the initial packaging design solution, Indicates the deformation loss cost reduced by the first alternative optimization scheme compared with the initial packaging design scheme, Indicates the expected deformation rate of the initial packaging design, represents the expected deformation rate of the first alternative optimization solution, m represents the number of target contents to be packaged, and q represents the cost of a single package; represents the increased cost of the second alternative optimization solution compared to the initial printing design solution, The second alternative optimization solution reduces the fading loss cost compared to the initial printing design solution. Indicates the expected fading rate of the initial printed design. represents the expected fading rate of the second alternative optimization solution.

9. A computer device comprising a processor and a memory connected in a signal connection, characterized in that: The memory stores at least one instruction or at least one program, and when the at least one instruction or the at least one program is loaded by the processor, the method for automatically matching and designing paper packaging in combination with cost according to any one of claims 1 to 7 is executed.

10. A computer-readable storage medium having stored thereon at least one instruction or at least one program, characterized in that: When the at least one instruction or the at least one program segment is loaded by the processor, the method for automatically matching and designing paper packaging in combination with cost as described in any one of claims 1 to 7 is executed.

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