CN113787759A - Intelligent selection method for production process of corrugated carton package - Google Patents
Intelligent selection method for production process of corrugated carton package Download PDFInfo
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- CN113787759A CN113787759A CN202111354979.9A CN202111354979A CN113787759A CN 113787759 A CN113787759 A CN 113787759A CN 202111354979 A CN202111354979 A CN 202111354979A CN 113787759 A CN113787759 A CN 113787759A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B31—MAKING ARTICLES OF PAPER, CARDBOARD OR MATERIAL WORKED IN A MANNER ANALOGOUS TO PAPER; WORKING PAPER, CARDBOARD OR MATERIAL WORKED IN A MANNER ANALOGOUS TO PAPER
- B31B—MAKING CONTAINERS OF PAPER, CARDBOARD OR MATERIAL WORKED IN A MANNER ANALOGOUS TO PAPER
- B31B50/00—Making rigid or semi-rigid containers, e.g. boxes or cartons
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B31—MAKING ARTICLES OF PAPER, CARDBOARD OR MATERIAL WORKED IN A MANNER ANALOGOUS TO PAPER; WORKING PAPER, CARDBOARD OR MATERIAL WORKED IN A MANNER ANALOGOUS TO PAPER
- B31B—MAKING CONTAINERS OF PAPER, CARDBOARD OR MATERIAL WORKED IN A MANNER ANALOGOUS TO PAPER
- B31B50/00—Making rigid or semi-rigid containers, e.g. boxes or cartons
- B31B50/006—Controlling; Regulating; Measuring; Improving safety
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B31—MAKING ARTICLES OF PAPER, CARDBOARD OR MATERIAL WORKED IN A MANNER ANALOGOUS TO PAPER; WORKING PAPER, CARDBOARD OR MATERIAL WORKED IN A MANNER ANALOGOUS TO PAPER
- B31B—MAKING CONTAINERS OF PAPER, CARDBOARD OR MATERIAL WORKED IN A MANNER ANALOGOUS TO PAPER
- B31B50/00—Making rigid or semi-rigid containers, e.g. boxes or cartons
- B31B50/74—Auxiliary operations
- B31B50/88—Printing; Embossing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
Abstract
The invention discloses an intelligent selection method for a production process of corrugated carton packages, wherein the method comprises the following steps: training the first carton process selection model through the printing attribute information and the first package application characteristic information to obtain a first reinforced carton process selection model; training the second carton process selection model through the physical attribute information to obtain a second reinforced carton process selection model; extracting first parameter information of a first reinforced carton process selection model and second parameter information of a second reinforced carton process selection model; constructing a third carton process selection model according to the first parameter information and the second parameter information; and selecting the production process of the first carton package according to a third carton process selection model to obtain a first corrugated carton package production process. The technical problem of prior art corrugated box production technology selection lack the pertinence, lead to influencing the carton packing application effect, and then cause the damage to the product is solved.
Description
Technical Field
The invention relates to the field of packaging processes, in particular to an intelligent selection method for a production process of corrugated carton packages.
Background
Corrugated paper boards are made into corrugated paper boxes through die cutting, indentation, box nailing or box gluing, the corrugated paper boxes belong to green and environment-friendly products, are beneficial to environmental protection and loading, unloading and transportation, are packaging products with the widest application, are always the first of various packaging products in use amount, and become the leading force of transportation and packaging with excellent service performance and good processing performance.
However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:
the prior art corrugated case production technology selection lacks the pertinence, leads to influencing the carton packing application effect, and then causes the technical problem of damage to the product.
Disclosure of Invention
The embodiment of the application provides an intelligent selection method for a production process of corrugated case packaging, solves the technical problems that the application effect of the carton packaging is influenced and further the product is damaged due to the lack of pertinence in the production process selection of the corrugated case in the prior art, achieves the technical effects that the carton process is specifically and individually selected by constructing a carton process selection model by combining the application attribute and the physical attribute of the carton, is more accurate and professional, improves the application effect of the carton packaging, and ensures the product quality.
In view of the above, the present invention has been developed to provide a method that overcomes, or at least partially solves, the above-mentioned problems.
In a first aspect, an embodiment of the present application provides a method for intelligently selecting a production process of a corrugated carton package, where the method includes: obtaining application attribute information and printing attribute information of a first carton package; acquiring first package application characteristic information according to the application attribute information; training a first carton process selection model through the printing attribute information and the first package application characteristic information to obtain a first reinforced carton process selection model; obtaining physical attribute information of a first carton package; training a second carton process selection model through the physical attribute information to obtain a second reinforced carton process selection model; extracting first parameter information of the first reinforced carton process selection model and second parameter information of the second reinforced carton process selection model; constructing a third carton process selection model according to the first parameter information and the second parameter information; and selecting the production process of the first carton package according to the third carton process selection model to obtain a first corrugated carton package production process.
In another aspect, the present application further provides a system for intelligently selecting a production process for a corrugated box package, the system comprising: a first obtaining unit for obtaining application attribute information and printing attribute information of a first carton package; a second obtaining unit, configured to obtain the application characteristic information of the first package according to the application attribute information; a third obtaining unit, configured to train a first carton process selection model according to the printing attribute information and the first package application characteristic information, and obtain a first reinforced carton process selection model; a fourth obtaining unit for obtaining physical attribute information of the first carton package; a fifth obtaining unit, configured to train the second carton process selection model according to the physical attribute information to obtain a second reinforced carton process selection model; a first extraction unit, configured to extract first parameter information of the first reinforced carton process selection model and second parameter information of the second reinforced carton process selection model; the first building unit is used for building a third carton process selection model according to the first parameter information and the second parameter information; and the sixth obtaining unit is used for selecting the production process of the first carton package according to the third carton process selection model to obtain the first corrugated carton package production process.
In a third aspect, an embodiment of the present invention provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored on the memory and executable on the processor, where the transceiver, the memory, and the processor are connected via the bus, and when the computer program is executed by the processor, the method for controlling output data includes any one of the steps described above.
In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps in the method for controlling output data according to any one of the above.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
due to the adoption of the method, the application attribute information and the printing attribute information of the first carton package are obtained; acquiring first package application characteristic information according to the application attribute information; training a first carton process selection model through the printing attribute information and the first package application characteristic information to obtain a first reinforced carton process selection model; obtaining physical attribute information of a first carton package; training a second carton process selection model through the physical attribute information to obtain a second reinforced carton process selection model; extracting first parameter information of the first reinforced carton process selection model and second parameter information of the second reinforced carton process selection model; constructing a third carton process selection model according to the first parameter information and the second parameter information; and selecting the production process of the first carton package according to the third carton process selection model to obtain a first corrugated carton package production process. And then, a carton process selection model is constructed by combining the application attributes and the physical attributes of the carton, the individual selection of the carton process is pertinently carried out, the carton process is more accurate and professional, the application effect of carton packaging is improved, and the technical effect of product quality is ensured.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
Fig. 1 is a schematic flow chart illustrating a method for intelligently selecting a manufacturing process for a corrugated box package according to an embodiment of the present disclosure;
fig. 2 is a schematic flow chart illustrating the process of obtaining application characteristic information of the carton package in the intelligent selection method for the production process of the corrugated carton package according to the embodiment of the present application;
fig. 3 is a schematic flow chart illustrating the determination of the appearance index of the carton package in the intelligent selection method for the production process of the corrugated carton package according to the embodiment of the present application;
fig. 4 is a schematic flow chart illustrating the process for obtaining the manufacturing dimension of the carton package in the method for intelligently selecting the production process of the corrugated carton package according to the embodiment of the present application;
fig. 5 is a schematic flow chart illustrating the process of obtaining application characteristic information of the carton package in the method for intelligently selecting a production process of the corrugated carton package according to the embodiment of the present application;
fig. 6 is a schematic flow chart illustrating the process selection model for determining the second reinforced carton process selection model in the intelligent selection method for the production process of corrugated carton packages according to the embodiment of the present application;
fig. 7 is a schematic flow chart illustrating a first reinforced carton process selection model obtained in an intelligent selection method for a corrugated carton package production process according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of a production process intelligence selection system for a corrugated box package in accordance with an embodiment of the present disclosure;
fig. 9 is a schematic structural diagram of an electronic device for executing a method of controlling output data according to an embodiment of the present application.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a fourth obtaining unit 14, a fifth obtaining unit 15, a first extracting unit 16, a first constructing unit 17, a sixth obtaining unit 18, a bus 1110, a processor 1120, a transceiver 1130, a bus interface 1140, a memory 1150, an operating system 1151, an application 1152 and a user interface 1160.
Detailed Description
In the description of the embodiments of the present invention, it should be apparent to those skilled in the art that the embodiments of the present invention can be embodied as methods, apparatuses, electronic devices, and computer-readable storage media. Thus, embodiments of the invention may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), a combination of hardware and software. Furthermore, in some embodiments, embodiments of the invention may also be embodied in the form of a computer program product in one or more computer-readable storage media having computer program code embodied in the medium.
The computer-readable storage media described above may take any combination of one or more computer-readable storage media. The computer-readable storage medium includes: an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of the computer-readable storage medium include: a portable computer diskette, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, a flash memory, an optical fiber, a compact disc read-only memory, an optical storage device, a magnetic storage device, or any combination thereof. In embodiments of the invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, device, or apparatus.
The method, the device and the electronic equipment are described through the flow chart and/or the block diagram.
It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions. These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing apparatus to function in a particular manner. Thus, the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
The embodiments of the present invention will be described below with reference to the drawings.
Example one
As shown in fig. 1, an embodiment of the present application provides a method for intelligently selecting a production process of a corrugated carton package, wherein the method includes:
step S100: obtaining application attribute information and printing attribute information of a first carton package;
specifically, the carton packaging refers to the packaging of products by paper boxes in the circulation process for protecting the products, facilitating storage and transportation and promoting sales, and is the most widely applied packaging mode. The carton packaging is different from wooden box packaging, woven bag packaging, cloth bag packaging and plastic box packaging, has the characteristics of easily obtained materials, light weight, easy printing, easy design and forming, low cost and the like, and is widely used for selling and packaging and transporting goods. The application attribute information of the first carton package comprises the application package type, the package number, the package size, the package weight and the like of the corrugated carton. The printing attribute information comprises a printing mode, a printing color, a printing pattern, printing ink and the like of the first carton package, and different carton package attributes and different carton processes are selected.
Step S200: acquiring first package application characteristic information according to the application attribute information;
as shown in fig. 2, further, in which, according to the application attribute information, the obtaining of the application characteristic information of the first package further includes:
step S210: determining a material index, an appearance index and a wear resistance index of the first carton package according to the application attribute information;
step S220: obtaining a first applied convolution characteristic of the material indicator, a second applied convolution characteristic of the appearance indicator, and a third applied convolution characteristic of the abrasion resistance indicator;
step S230: and obtaining the first package application characteristic information according to the first application convolution characteristic, the second application convolution characteristic and the third application convolution characteristic.
Specifically, according to the application attribute information, corresponding first package application characteristic information is obtained, the first package application characteristic information is corrugated carton package application characteristics, and it is ensured that each characteristic index of carton packages can meet application effects. And determining a material index, an appearance index and a wear-resistant strength index of the first carton package according to the application attribute information. The material index is the raw paper material of the corrugated case, the grades of the corrugated raw paper can be divided into four types, namely A grade, B grade, C grade and D grade according to the national standard, the grades are different, the application effects are different, and the corrugated raw paper has the characteristics that: long fiber, heavy sizing, high physical strength, rough paperboard, different application approaches, and different raw paper materials. The appearance indexes are appearance characteristics of the corrugated case, including size, smoothness, whiteness, case edge shape and the like of the case, and can be determined according to customer requirements, different packaging applications and different appearance requirements of the case. The wear-resistant strength index is the wear-resistant performance of the corrugated case, the higher the wear-resistant strength index is, the better the wear-resistant performance of the case package is, the wear-resistant strength is required to meet the strength requirement of the product in the transportation process, and the product damage caused by insufficient wear-resistant strength is avoided.
The convolutional neural network is a deep feedforward neural network with the characteristics of local connection, weight sharing and the like, has a remarkable effect in the field of image and video analysis, such as various visual tasks of image classification, target detection, image segmentation and the like, and is one of the most widely applied models at present. A convolutional neural network, literally comprising two parts: convolution + neural network. The convolution is a feature extractor, and the neural network can be regarded as a classifier. A convolutional neural network is trained, namely a feature extractor (convolution) and a subsequent classifier (neural network) are trained simultaneously. And extracting and classifying the index features through a convolutional neural network to obtain the corresponding application convolution features of the material index, the appearance index and the wear-resistant strength index. And obtaining a convolution calculation analysis result, namely first package application characteristic information, according to the traversal convolution operation of the first application convolution characteristic, the second application convolution characteristic and the third application convolution characteristic. The application characteristics of the corrugated case are analyzed in a convolutional neural network mode so as to achieve the technical effect of more accurate training of the subsequent case packaging process selection model.
Step S300: training a first carton process selection model through the printing attribute information and the first package application characteristic information to obtain a first reinforced carton process selection model;
specifically, a first carton process selection model is trained according to the printing attribute information and the first package application characteristic information, the first carton process selection model is a neural network model and is obtained by training basic production process data of the corrugated carton, for example, the corrugated carton production line is an automatic operation of manufacturing the corrugated carton by printing, slotting, die cutting, creasing, nailing or gluing and packaging corrugated cardboards. And training a first carton process selection model through the printing attribute information and the first package application characteristic information, namely performing incremental learning on the first carton process selection model, wherein the first carton process selection model is obtained by forming a neural network by connecting a plurality of neurons. Therefore, the first reinforced carton process selection model obtained through the training of the loss data reserves the basic function of the first carton process selection model and maintains the performance of continuous updating of the model, so that the updating performance of the process selection is improved, and the accuracy and the personalized technical effect of the carton process selection are ensured.
Step S400: obtaining physical attribute information of a first carton package;
step S500: training a second carton process selection model through the physical attribute information to obtain a second reinforced carton process selection model;
specifically, the physical attribute information of the first carton package is the physical performance of the corrugated carton package, including parameters such as carton tightness, density, ring crush strength, positive/negative water absorption and folding endurance, a second carton process selection model is trained through the physical attribute information, the second carton process selection model is a carton process selection model matched with the physical attribute information, a second reinforced carton process selection model after model updating is obtained, the performance of model updating is maintained, and the updating performance of carton packaging process selection is improved.
Step S600: extracting first parameter information of the first reinforced carton process selection model and second parameter information of the second reinforced carton process selection model;
step S700: constructing a third carton process selection model according to the first parameter information and the second parameter information;
specifically, first parameter information of the first reinforced carton process selection model, such as carton printing parameters, material parameters, wear index parameters and the like, is extracted, and second parameter information of the second reinforced carton process selection model, such as carton water absorption parameters, folding endurance parameters, density parameters and the like, is extracted. And constructing a third carton process selection model after model updating according to the first parameter information and the second parameter information, so that the updated carton process selection model is more accurate and professional, and further the carton process is selected in a targeted manner.
Step S800: and selecting the production process of the first carton package according to the third carton process selection model to obtain a first corrugated carton package production process.
Specifically, the production process of the first carton package is selected according to the third carton process selection model, the third carton process selection model is a neural network model, and a training output result of the model, namely the first corrugated carton package production process, is obtained. The carton process selection model is constructed by combining the application attributes and the physical attributes of the carton, the individual selection of the carton process is pertinently carried out, the specialization is more accurate, the application effect of carton packaging is improved, and therefore the quality of packaged products is guaranteed.
As shown in fig. 3, further, in step S220 of the present embodiment of the application, the appearance index further includes:
step S221: obtaining first carton packaging size information and first carton packaging smoothness information according to the application attribute information;
step S222: carrying out grade division on the application attribute information according to a preset division rule to obtain a first package application grade;
step S223: determining a first carton packaging edge shape index according to the first packaging application grade;
step S224: determining an appearance indicator of the first carton package according to the first carton package size information, the first carton package smoothness information, and the first carton package flute indicator.
Specifically, according to the application attribute information, first carton package size information is obtained, wherein the first carton package size information is a carton package inner size and depends on the maximum outer size of the inner packing materials, the number and packing arrangement of the inner packing materials and the types of the inner packing materials. The first carton packaging smoothness information is the smoothness of the carton packaging surface, the smoothness is one of important factors influencing the printing quality of the carton packaging, and the requirements on the carton packaging smoothness are different in different application ways. And grading the application attribute information according to a preset grading rule, wherein the preset grading rule is used for grading the application grade of the carton package, and if the carton package is more noble and fragile products, the application grade of the carton package is correspondingly higher. And determining a first carton packaging corrugated index according to the first packaging application grade, wherein the first carton packaging corrugated index is the corrugated shape of the corrugated carton, comprises a U shape, a V shape and a UV shape, is universal in the market, has different corrugated shapes and has different protection strength on the packaged product. Determining an appearance indicator of the first carton package jointly according to the first carton package size information, the first carton package smoothness information, and the first carton package flute indicator. The appearance index of the carton package is determined by multiple factors, so that the index is more accurately obtained, and the technical effect of the product packaging quality is ensured.
As shown in fig. 4, further, step S224 in this embodiment of the present application further includes:
step S2241: determining a first carton package manufacturing factor based on the first package application level;
step S2242: determining a first paperboard thickness according to the first carton packaging flute index and the material index;
step S2243: constructing a carton package manufacturing size formula:
wherein, in the step (A),
packing the size information for the first carton,
is the first thickness of the paperboard sheet,
manufacturing a coefficient for a first carton package;
step S2244: inputting the first carton package size information, the first carton package manufacturing coefficient and the first paperboard thickness into the manufacturing size formula to obtain a first carton package manufacturing size;
step S2245: supplementing the appearance index according to the first carton package manufacturing size.
Specifically, the first carton package manufacturing factor is a corrugated carton package production loss factor, and generally depends on the first package application level, i.e., the number of layers and the material of the paperboard. And determining the first paperboard thickness of the corrugated carton according to the first carton packaging prismatic index and the material index. Constructing a carton package manufacturing size formula:
wherein, in the step (A),
packing the size information for the first carton,
is the first thickness of the paperboard sheet,
a manufacturing factor for the first carton package. Inputting the first carton package size information, the first carton package manufacturing coefficient and the first paperboard thickness into the manufacturing size formula to obtain a calculation output result of the formula, namely a first carton package manufacturing size, wherein the first carton package manufacturing size is a corrugated carton package production manufacturing size. According to the first carton package manufacturing size, the appearance indexes are supplemented, so that the carton package sizes of the appearance indexes are more comprehensive and accurate, and the application effect of the corrugated carton package is ensured.
As shown in fig. 5, further, in which, according to the first application convolution feature, the second application convolution feature, and the third application convolution feature, the obtaining of the first package application characteristic information further includes:
step S231: taking the material indicator as a first target feature, the appearance indicator as a second target feature, and the abrasion resistance indicator as a third target feature;
step S232: performing traversal convolution operation on the first application convolution feature and the first target feature, the second application convolution feature and the second target feature, and the third application convolution feature and the third target feature respectively to obtain a corresponding first convolution result, a corresponding second convolution result and a corresponding third convolution result;
step S233: and performing result fusion analysis on the first convolution result, the second convolution result and the third convolution result to obtain the first package application characteristic information.
Specifically, the material index, the appearance index and the wear resistance index are respectively used as application target features of a corrugated case, traversal convolution operation is respectively performed on the first application convolution feature, the first target feature, the second application convolution feature, the second target feature and the third application convolution feature, corresponding first convolution result, second convolution result and third convolution result can be obtained, fusion analysis is performed on the first convolution result, the second convolution result, the third convolution result and the fourth convolution result, and first package application characteristic information is generated and is a result obtained after feature training is performed on a convolutional neural network. The application characteristics of the corrugated case are calculated and analyzed in a convolutional neural network mode so that the following training of a case packaging process selection model is more accurate, and therefore the case packaging application effect is guaranteed.
As shown in fig. 6, further, the steps of the embodiment of the present application further include:
step S910: constructing a carton process selection model library;
step S920: obtaining a first physical parameter information set according to the physical attribute information of the first carton package;
step S930: and determining a second reinforced carton process selection model from the carton process selection model library according to the first physical parameter information set.
Specifically, the carton process selection model base is a model database selected by a corrugated carton production process, and comprises carton physical attributes, printing attributes, application attributes and the like, and a first physical parameter information set is obtained according to physical attribute information of the first carton package, wherein the first physical parameter information set comprises parameters such as carton tightness, density, ring crush strength, positive/negative water absorption, folding endurance and the like. And according to the first physical parameter information set, performing data matching in the carton technology selection model library, and selecting a second reinforced carton technology selection model for calling parameter matching from the carton technology selection model library for selecting the production technology of the corrugated carton. The model is selected by matching the production process suitable for the physical parameters of the carton, so that the data in the subsequent model training is more accurate, and the technical effect of the product packaging quality is ensured.
As shown in fig. 7, further, in which the first carton process selection model is trained through the printing attribute information and the first package application characteristic information to obtain a first reinforced carton process selection model, step S300 of this embodiment of the present application further includes:
step S310: inputting the printing attribute information and the first package application characteristic information into the first carton process selection model to obtain a first prediction process selection result;
step S320: performing data enhancement analysis on the first prediction process selection result to obtain first enhancement data;
step S330: and updating the first carton process selection model through the first reinforced data to obtain a first reinforced carton process selection model.
Specifically, the first prediction process selection result is a corresponding prediction process selection result obtained by performing carton process selection in the first carton process selection model based on the printing attribute information and the first package application characteristic information, data loss analysis is completed by introducing a loss function, so as to obtain corresponding first reinforcement data, where the first reinforcement data is data knowledge loss data representing relevant data of the first carton process selection model for the printing attribute information and the first package application characteristic information, and incremental learning of the first carton process selection model is completed based on the first reinforcement data, and since the first carton process selection model is obtained by connecting a plurality of neurons with each other to form a neural network, the first reinforcement carton process selection model retains the basic function of the first carton process selection model through training of the reinforcement data, and the continuous updating performance of the model is maintained, so that the updating performance of the process selection is improved, and the technical effect of the accuracy of the process selection result of the carton is ensured.
To sum up, the production process intelligent selection method for the corrugated carton package provided by the embodiment of the application has the following technical effects:
due to the adoption of the method, the application attribute information and the printing attribute information of the first carton package are obtained; acquiring first package application characteristic information according to the application attribute information; training a first carton process selection model through the printing attribute information and the first package application characteristic information to obtain a first reinforced carton process selection model; obtaining physical attribute information of a first carton package; training a second carton process selection model through the physical attribute information to obtain a second reinforced carton process selection model; extracting first parameter information of the first reinforced carton process selection model and second parameter information of the second reinforced carton process selection model; constructing a third carton process selection model according to the first parameter information and the second parameter information; and selecting the production process of the first carton package according to the third carton process selection model to obtain a first corrugated carton package production process. And then, a carton process selection model is constructed by combining the application attributes and the physical attributes of the carton, the individual selection of the carton process is pertinently carried out, the carton process is more accurate and professional, the application effect of carton packaging is improved, and the technical effect of product quality is ensured.
Example two
Based on the same inventive concept as the method for intelligently selecting the production process of the corrugated carton package in the previous embodiment, the invention also provides a system for intelligently selecting the production process of the corrugated carton package, as shown in fig. 8, the system comprises:
a first obtaining unit 11, wherein the first obtaining unit 11 is used for obtaining application attribute information and printing attribute information of a first carton package;
a second obtaining unit 12, where the second obtaining unit 12 is configured to obtain the first package application characteristic information according to the application attribute information;
a third obtaining unit 13, where the third obtaining unit 13 is configured to train a first carton process selection model through the printing attribute information and the first package application characteristic information, and obtain a first reinforced carton process selection model;
a fourth obtaining unit 14, wherein the fourth obtaining unit 14 is used for obtaining the physical attribute information of the first carton package;
a fifth obtaining unit 15, where the fifth obtaining unit 15 is configured to train the second carton process selection model through the physical attribute information to obtain a second reinforced carton process selection model;
a first extraction unit 16, where the first extraction unit 16 is configured to extract first parameter information of the first reinforced carton process selection model and second parameter information of the second reinforced carton process selection model;
a first building unit 17, where the first building unit 17 is configured to build a third carton process selection model according to the first parameter information and the second parameter information;
a sixth obtaining unit 18, where the sixth obtaining unit 18 is configured to select the production process of the first carton package according to the third carton process selection model, so as to obtain a first production process of the corrugated carton package.
Further, the system further comprises:
a first determination unit for determining a material index, an appearance index, and a wear-resistance index of the first carton package according to the application attribute information;
a seventh obtaining unit configured to obtain a first applied convolution feature of the material indicator, a second applied convolution feature of the appearance indicator, and a third applied convolution feature of the abrasion resistance indicator;
an eighth obtaining unit, configured to obtain first package application characteristic information according to the first application convolution feature, the second application convolution feature, and the third application convolution feature.
Further, the system further comprises:
a ninth obtaining unit configured to obtain first carton package size information and first carton package smoothness information according to the application attribute information;
a tenth obtaining unit, configured to perform level division on the application attribute information according to a predetermined division rule, and obtain a first package application level;
a second determination unit for determining a first carton package flute index according to the first package application level;
a third determination unit configured to determine an appearance index of the first carton package according to the first carton package size information, the first carton package smoothness information, and the first carton package edge index.
Further, the system further comprises:
a fourth determination unit for determining a first carton package manufacturing factor according to the first package application level;
a fifth determination unit for determining a first paperboard thickness based on the first carton package flute index and the material index;
a second building unit for building a carton package manufacturing size formula:
wherein, in the step (A),
packing the size information for the first carton,
is the first thickness of the paperboard sheet,
manufacturing a coefficient for a first carton package;
an eleventh obtaining unit, configured to input the first carton package size information, the first carton package manufacturing coefficient, and the first paperboard thickness into the manufacturing size formula, and obtain a first carton package manufacturing size;
a first replenishment unit for replenishing the appearance index according to the first carton package manufacturing size.
Further, the system further comprises:
a first feature unit for using the material index as a first target feature, the appearance index as a second target feature, and the abrasion resistance index as a third target feature;
a twelfth obtaining unit, configured to perform traversal convolution operations on the first application convolution feature and the first target feature, the second application convolution feature and the second target feature, and the third application convolution feature and the third target feature, respectively, to obtain a corresponding first convolution result, a corresponding second convolution result, and a corresponding third convolution result;
a thirteenth obtaining unit, configured to perform result fusion analysis on the first convolution result, the second convolution result, and the third convolution result, so as to obtain first package application characteristic information.
Further, the system further comprises:
a third building unit for building a carton process selection model library;
a fourteenth obtaining unit, configured to obtain a first physical parameter information set according to the physical attribute information of the first carton package;
a sixth determining unit for determining a second carton process selection model from the library of carton process selection models according to the first set of physical parameter information.
Further, the system further comprises:
a fifteenth obtaining unit, configured to input the printing attribute information and the first package application characteristic information into the first carton process selection model, and obtain a first predicted process selection result;
a sixteenth obtaining unit, configured to perform data enhancement analysis on the first prediction process selection result to obtain first enhancement data;
a seventeenth obtaining unit, configured to update the first carton technology selection model according to the first reinforcement data, and obtain a first reinforced carton technology selection model.
Various modifications and specific examples of the method for intelligently selecting a manufacturing process of a corrugated box package in the first embodiment of fig. 1 are also applicable to the system for intelligently selecting a manufacturing process of a corrugated box package of the present embodiment, and the implementation of the system for intelligently selecting a manufacturing process of a corrugated box package in the present embodiment will be apparent to those skilled in the art from the foregoing detailed description of the method for intelligently selecting a manufacturing process of a corrugated box package, and therefore, for the sake of brevity of the description, detailed description thereof will not be provided herein.
In addition, an embodiment of the present invention further provides an electronic device, which includes a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the transceiver, the memory, and the processor are connected via the bus, and when the computer program is executed by the processor, the processes of the method for controlling output data are implemented, and the same technical effects can be achieved, and are not described herein again to avoid repetition.
Specifically, referring to fig. 9, an embodiment of the present invention further provides an electronic device, which includes a bus 1110, a processor 1120, a transceiver 1130, a bus interface 1140, a memory 1150, and a user interface 1160.
In an embodiment of the present invention, the electronic device further includes: a computer program stored on the memory 1150 and executable on the processor 1120, the computer program, when executed by the processor 1120, implementing the various processes of the method embodiments of controlling output data described above.
A transceiver 1130 for receiving and transmitting data under the control of the processor 1120.
In embodiments of the invention in which a bus architecture (represented by bus 1110) is used, bus 1110 may include any number of interconnected buses and bridges, with bus 1110 connecting various circuits including one or more processors, represented by processor 1120, and memory, represented by memory 1150.
The bus 1110 may also connect various other circuits such as peripherals, voltage regulators, or power management circuits to provide an interface between the bus 1110 and the transceiver 1130, as is well known in the art. Therefore, the embodiments of the present invention will not be further described.
The transceiver 1130 may be one element or may be multiple elements, such as multiple receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. For example: the transceiver 1130 receives external data from other devices, and the transceiver 1130 transmits data processed by the processor 1120 to other devices. Depending on the nature of the computer device, a user interface 1160 may also be provided, such as: touch screen, physical keyboard, display, mouse, speaker, microphone, trackball, joystick, stylus.
It is to be appreciated that in embodiments of the invention, the memory 1150 may further include memory located remotely with respect to the processor 1120, which may be coupled to a server via a network. One or more portions of the above-described network may be an ad hoc network, an intranet, an extranet, a virtual private network, a local area network, a wireless local area network, a wide area network, a wireless wide area network, a metropolitan area network, the internet, a public switched telephone network, a plain old telephone service network, a cellular telephone network, a wireless fidelity network, and a combination of two or more of the above. For example, the cellular telephone network and the wireless network may be global mobile communications devices, code division multiple access devices, global microwave interconnect access devices, general packet radio service devices, wideband code division multiple access devices, long term evolution devices, LTE frequency division duplex devices, LTE time division duplex devices, long term evolution advanced devices, universal mobile communications devices, enhanced mobile broadband devices, mass machine type communications devices, ultra-reliable low-latency communications devices, and the like.
It is to be understood that the memory 1150 in embodiments of the present invention can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. Wherein the nonvolatile memory includes: read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, or flash memory.
The volatile memory includes: random access memory, which acts as an external cache. By way of example, and not limitation, many forms of RAM are available, such as: static random access memory, dynamic random access memory, synchronous dynamic random access memory, double data rate synchronous dynamic random access memory, enhanced synchronous dynamic random access memory, synchronous link dynamic random access memory, and direct memory bus random access memory. The memory 1150 of the electronic device described in the embodiments of the invention includes, but is not limited to, the above and any other suitable types of memory.
In an embodiment of the present invention, memory 1150 stores the following elements of operating system 1151 and application programs 1152: an executable module, a data structure, or a subset thereof, or an expanded set thereof.
Specifically, the operating system 1151 includes various device programs, such as: a framework layer, a core library layer, a driver layer, etc. for implementing various basic services and processing hardware-based tasks. Applications 1152 include various applications such as: media player, browser, used to realize various application services. A program implementing a method of an embodiment of the invention may be included in application program 1152. The application programs 1152 include: applets, objects, components, logic, data structures, and other computer device-executable instructions that perform particular tasks or implement particular abstract data types.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements each process of the above method for controlling output data, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.
The above description is only a specific implementation of the embodiments of the present invention, but the scope of the embodiments of the present invention is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the embodiments of the present invention, and all such changes or substitutions should be covered by the scope of the embodiments of the present invention. Therefore, the protection scope of the embodiments of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method for intelligently selecting a production process for a corrugated box package, the method comprising:
obtaining application attribute information and printing attribute information of a first carton package;
acquiring first package application characteristic information according to the application attribute information;
training a first carton process selection model through the printing attribute information and the first package application characteristic information to obtain a first reinforced carton process selection model;
obtaining physical attribute information of a first carton package;
training a second carton process selection model through the physical attribute information to obtain a second reinforced carton process selection model;
extracting first parameter information of the first reinforced carton process selection model and second parameter information of the second reinforced carton process selection model;
constructing a third carton process selection model according to the first parameter information and the second parameter information;
and selecting the production process of the first carton package according to the third carton process selection model to obtain a first corrugated carton package production process.
2. The method of claim 1, wherein the obtaining first package application characteristic information according to the application attribute information comprises:
determining a material index, an appearance index and a wear resistance index of the first carton package according to the application attribute information;
obtaining a first applied convolution characteristic of the material indicator, a second applied convolution characteristic of the appearance indicator, and a third applied convolution characteristic of the abrasion resistance indicator;
and obtaining the first package application characteristic information according to the first application convolution characteristic, the second application convolution characteristic and the third application convolution characteristic.
3. The method of claim 2, wherein the appearance metrics comprise:
obtaining first carton packaging size information and first carton packaging smoothness information according to the application attribute information;
carrying out grade division on the application attribute information according to a preset division rule to obtain a first package application grade;
determining a first carton packaging edge shape index according to the first packaging application grade;
determining an appearance indicator of the first carton package according to the first carton package size information, the first carton package smoothness information, and the first carton package flute indicator.
4. The method of claim 3, wherein the method comprises:
determining a first carton package manufacturing factor based on the first package application level;
determining a first paperboard thickness according to the first carton packaging flute index and the material index;
y = (a +2b) -k, wherein a is first carton package size information, b is a first paperboard thickness, and k is a first carton package manufacturing coefficient;
inputting the first carton package size information, the first carton package manufacturing coefficient and the first paperboard thickness into the manufacturing size formula to obtain a first carton package manufacturing size;
supplementing the appearance index according to the first carton package manufacturing size.
5. The method of claim 2, wherein said obtaining first package application characteristic information based on said first application convolution characteristic, said second application convolution characteristic, and said third application convolution characteristic comprises:
taking the material indicator as a first target feature, the appearance indicator as a second target feature, and the abrasion resistance indicator as a third target feature;
performing traversal convolution operation on the first application convolution feature and the first target feature, the second application convolution feature and the second target feature, and the third application convolution feature and the third target feature respectively to obtain a corresponding first convolution result, a corresponding second convolution result and a corresponding third convolution result;
and performing result fusion analysis on the first convolution result, the second convolution result and the third convolution result to obtain the first package application characteristic information.
6. The method of claim 1, wherein the method comprises:
constructing a carton process selection model library;
obtaining a first physical parameter information set according to the physical attribute information of the first carton package;
and determining a second carton process selection model from the carton process selection model library according to the first physical parameter information set.
7. The method of claim 1, wherein said training a first carton process selection model with said print attribute information and said first package application characteristic information to obtain a first reinforced carton process selection model comprises:
inputting the printing attribute information and the first package application characteristic information into the first carton process selection model to obtain a first prediction process selection result;
performing data enhancement analysis on the first prediction process selection result to obtain first enhancement data;
and updating the first carton process selection model through the first reinforced data to obtain a first reinforced carton process selection model.
8. A system for intelligently selecting a manufacturing process for a corrugated box package, the system comprising:
a first obtaining unit for obtaining application attribute information and printing attribute information of a first carton package;
a second obtaining unit, configured to obtain the application characteristic information of the first package according to the application attribute information;
a third obtaining unit, configured to train a first carton process selection model according to the printing attribute information and the first package application characteristic information, and obtain a first reinforced carton process selection model;
a fourth obtaining unit for obtaining physical attribute information of the first carton package;
a fifth obtaining unit, configured to train the second carton process selection model according to the physical attribute information to obtain a second reinforced carton process selection model;
a first extraction unit, configured to extract first parameter information of the first reinforced carton process selection model and second parameter information of the second reinforced carton process selection model;
the first building unit is used for building a third carton process selection model according to the first parameter information and the second parameter information;
and the sixth obtaining unit is used for selecting the production process of the first carton package according to the third carton process selection model to obtain the first corrugated carton package production process.
9. An electronic device for intelligent selection of a production process for corrugated cardboard boxes packages, comprising a bus, a transceiver, a memory, a processor and a computer program stored on the memory and executable on the processor, the transceiver, the memory and the processor being connected via the bus, characterized in that the computer program realizes the steps of the method as claimed in any one of claims 1-7 when executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1-7.
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