CN112487780A - Order data typesetting optimization method and system - Google Patents
Order data typesetting optimization method and system Download PDFInfo
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Abstract
The invention discloses an order data typesetting optimization method and system, wherein first order information is obtained through a first camera device; obtaining first preset classification information; judging whether the first order information is complete or not; obtaining a first classification optimization instruction; according to a first classification optimization instruction, obtaining a first optimization result of a first order through the first preset classification information; obtaining plate graphic information of the first order according to the first optimization result and using the plate graphic information as first input information; acquiring first machine information according to the first order information and using the first machine information as second input information; and inputting the first input information and the second input information into a first training model to obtain a first output result of the first training model, and replacing the first order information with the first optimization result and the first plate figure arrangement result according to a first replacement instruction. The method solves the technical problems that in the prior art, the order typesetting optimization is inaccurate, the efficiency is low, and the order subjected to optimization processing cannot be more fit with a machine.
Description
Technical Field
The invention relates to the related field of order data typesetting optimization, in particular to an order data typesetting optimization method and system.
Background
The order refers to the fact that the purchasing department of the enterprise sends out order proof (including all purchasing processes of finished products, raw materials, fuel, parts, office supplies, services and the like) to the supplier. The formats of orders of different companies are different, and the order typesetting optimization is carried out manually at the present stage, so that the efficiency is low, and the order typesetting is not scientific and accurate enough.
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 technical problems that the order typesetting optimization is inaccurate, the efficiency is low, and the order subjected to the optimization processing cannot be more fit with a machine table exist in the prior art.
Disclosure of Invention
The embodiment of the application provides an order data typesetting optimization method and system, solves the technical problems that in the prior art, order typesetting optimization is inaccurate, efficiency is low, and an optimized order cannot be matched with a machine more, and achieves the purposes of accurately and quickly optimizing according to order content, so that order distribution is more suitable for the machine and the technical effect of improving processing efficiency is achieved.
In view of the above problems, the present application provides an order data layout optimization method and system.
In a first aspect, an embodiment of the present application provides an order data layout optimization method, where the method is applied to a furniture order data processing system, where the furniture order data processing system includes a first camera device, where the method includes: acquiring first order information through the first camera device; obtaining first preset classification information; judging whether the first order information is complete or not according to the first preset classification information; when the first order information is complete, obtaining a first classification optimization instruction; according to the first classification optimization instruction, obtaining a first optimization result of the first order through the first preset classification information; obtaining plate graphical information of the first order according to the first optimization result, and taking the plate graphical information as first input information; obtaining first machine information according to the first order information, and taking the first machine information as second input information; inputting the first input information and the second input information into a first training model, wherein the first training model is obtained by training a plurality of groups of training data, and each group of the plurality of groups of training data comprises: the first input information, the second input information and the identification information for identifying the plate figure arrangement result; obtaining a first output result of the first training model, wherein the first output result comprises a first plate graph arrangement result; and obtaining a first replacement instruction, and replacing the first order information with the first optimization result and the first plate figure arrangement result according to the first replacement instruction.
On the other hand, the application also provides an order data layout optimization system, which comprises: the first obtaining unit is used for obtaining first order information through a first camera device; a second obtaining unit, configured to obtain first preset classification information; the first judging unit is used for judging whether the first order information is complete or not through the first preset classification information; a third obtaining unit, configured to obtain a first classification optimization instruction when the first order information is complete; a fourth obtaining unit, configured to obtain, according to the first classification optimization instruction, a first optimization result of the first order according to the first preset classification information; a fifth obtaining unit, configured to obtain, according to the first optimization result, plate graphical information of the first order, and use the plate graphical information as first input information; a sixth obtaining unit, configured to obtain first station information according to the first order information, and use the first station information as second input information; a first input unit, configured to input the first input information and the second input information into a first training model, where the first training model is obtained by training multiple sets of training data, and each of the multiple sets of training data includes: the first input information, the second input information and the identification information for identifying the plate figure arrangement result; a seventh obtaining unit, configured to obtain a first output result of the first training model, where the first output result includes a first plate graph arrangement result; and the eighth obtaining unit is used for obtaining a first replacing instruction and replacing the first order information with the first optimization result and the first plate figure arrangement result according to the first replacing instruction.
In a third aspect, the present invention provides an order data layout optimization system, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of the first aspect when executing the program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the first order information is obtained through the first camera device, the order data is classified and optimized according to first preset classification information, the plate graphic information of the first order is obtained according to the optimized first optimization result and is used as first input information, the first machine station information is used as second input information, the first input information and the second input information are input into a first training model, the first plate graphic arrangement result is obtained based on the characteristic that the training model continuously corrects and adjusts by self, the first order information is replaced by the first optimization result and the first plate graphic arrangement result, the data meeting the first preset classification and the optimization result of the plate graphic suitable for machine station processing are obtained through the typesetting of the order and the rapid optimization processing of the plate graphic of the order, and the order distribution is more suitable for the machine station, the technical effect of improving the processing efficiency is achieved.
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 flowchart of a method for optimizing order data layout according to an embodiment of the present disclosure;
FIG. 2 is a schematic structural diagram of an order data layout optimization system according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a first judging unit 13, a third obtaining unit 14, a fourth obtaining unit 15, a fifth obtaining unit 16, a sixth obtaining unit 17, a first input unit 18, a seventh obtaining unit 19, an eighth obtaining unit 20, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, and a bus interface 306.
Detailed Description
The embodiment of the application provides an order data typesetting optimization method and system, solves the technical problems that in the prior art, order typesetting optimization is inaccurate, efficiency is low, and an optimized order cannot be matched with a machine more, and achieves the purposes of accurately and quickly optimizing according to order content, so that order distribution is more suitable for the machine and the technical effect of improving processing efficiency is achieved. Hereinafter, example embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are merely some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited to the example embodiments described herein.
Summary of the application
The order refers to the fact that the purchasing department of the enterprise sends out order proof (including all purchasing processes of finished products, raw materials, fuel, parts, office supplies, services and the like) to the supplier. The formats of orders of different companies are different, and the order typesetting optimization is carried out manually at the present stage, so that the efficiency is low, and the order typesetting is not scientific and accurate enough. The technical problems that the order typesetting optimization is inaccurate, the efficiency is low, and the order subjected to the optimization processing cannot be more fit with a machine table exist in the prior art.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the embodiment of the application provides an order data typesetting optimization method, which is applied to a furniture order data processing system, wherein the furniture order data processing system comprises a first camera device, and the method comprises the following steps: acquiring first order information through the first camera device; obtaining first preset classification information; judging whether the first order information is complete or not according to the first preset classification information; when the first order information is complete, obtaining a first classification optimization instruction; according to the first classification optimization instruction, obtaining a first optimization result of the first order through the first preset classification information; obtaining plate graphical information of the first order according to the first optimization result, and taking the plate graphical information as first input information; obtaining first machine information according to the first order information, and taking the first machine information as second input information; inputting the first input information and the second input information into a first training model, wherein the first training model is obtained by training a plurality of groups of training data, and each group of the plurality of groups of training data comprises: the first input information, the second input information and the identification information for identifying the plate figure arrangement result; obtaining a first output result of the first training model, wherein the first output result comprises a first plate graph arrangement result; and obtaining a first replacement instruction, and replacing the first order information with the first optimization result and the first plate figure arrangement result according to the first replacement instruction.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
As shown in fig. 1, an embodiment of the present application provides an order data layout optimization method, which is applied to a furniture order data processing system, where the furniture order data processing system includes a first camera device, where the method includes:
step S100: acquiring first order information through the first camera device;
specifically, the furniture order data processing system is a system for performing data processing on a furniture order, the first camera device is a camera device capable of scanning a barcode, the order barcode is scanned by the first camera device, and corresponding order data information is called, that is, first order information is obtained.
Step S200: obtaining first preset classification information;
specifically, the first preset classification is first preset classification information set according to the actual situation of applying the furniture order processing system.
Step S300: judging whether the first order information is complete or not according to the first preset classification information;
specifically, whether the item of the first order information is complete is judged according to the classified item of the first preset classification information and the obtained data information of the first order, and when the item of the first order information is complete, the following instructions are continued.
Step S400: when the first order information is complete, obtaining a first classification optimization instruction;
step S500: according to the first classification optimization instruction, obtaining a first optimization result of the first order through the first preset classification information;
specifically, when the first order information is detected to be complete, a first classification optimization instruction is obtained, and according to the first classification optimization instruction, the data information of the first order is optimized according to the first preset classification information, so that a first optimization result is obtained.
Step S600: obtaining plate graphical information of the first order according to the first optimization result, and taking the plate graphical information as first input information;
specifically, the first optimization result includes the optimized data result and the non-optimized plate graphic information in the first order, the plate graphic information summarized by the first optimization result is obtained, and the information is used as first input information.
Step S700: obtaining first machine information according to the first order information, and taking the first machine information as second input information;
specifically, the machine information is machine information of a requirement for glue spraying according to the first order, and the machine information includes size information of an actual working area of the machine and the like.
Step S800: inputting the first input information and the second input information into a first training model, wherein the first training model is obtained by training a plurality of groups of training data, and each group of the plurality of groups of training data comprises: the first input information, the second input information and the identification information for identifying the plate figure arrangement result;
step S900: and obtaining a first output result of the first training model, wherein the first output result comprises a first plate figure arrangement result.
Specifically, the first training model, namely a Neural network model in machine learning, Neural Network (NN), is a complex Neural network system formed by a large number of simple processing units (called neurons) widely connected with each other, reflects many basic features of human brain functions, and is a highly complex nonlinear dynamical learning system. Neural network models are described based on mathematical models of neurons. Artificial Neural Networks (Artificial Neural Networks) are a description of the first-order properties of the human brain system. Briefly, it is a mathematical model. And inputting the first input information and the second input information into a neural network model through training of a large amount of training data, and outputting a first plate figure arrangement result.
Furthermore, the training process is essentially a supervised learning process, each group of supervised data comprises first input information, second input information and identification information for identifying the plate figure arrangement result, the first input information and the second input information are input into the neural network model, the neural network model is continuously self-corrected and adjusted according to the identification information for identifying the plate figure arrangement result, and the group of supervised learning is ended and the next group of supervised learning is carried out until the obtained output result is consistent with the identification information; and when the output information of the neural network model reaches the preset accuracy rate/reaches the convergence state, finishing the supervised learning process. Through the supervised learning of the neural network model, the neural network model can process the input information more accurately, and a first plate figure arrangement result more suitable for a machine to process can be obtained.
Step S1000: and obtaining a first replacement instruction, and replacing the first order information with the first optimization result and the first plate figure arrangement result according to the first replacement instruction.
Specifically, a first replacement instruction is obtained according to an output result of the first training model, the first order information is replaced by the first optimization result and the first plate graph arrangement result according to the replacement instruction, and data meeting a first preset classification and an optimization result of plate graphs suitable for machine processing are obtained through typesetting of orders and rapid optimization processing of order plate graphs, so that order distribution is more suitable for machines, and the technical effect of improving processing efficiency is achieved.
Further, step S100 in the embodiment of the present application further includes:
step S110: obtaining first data of a first order through the first order information;
step S120: judging whether the first order information has second data or not;
step S130: when the first check instruction exists, obtaining a first check instruction;
step S140: according to the first checking instruction, checking the first data and the second data;
step S150: and obtaining a first verification result, and taking the first verification result as first order information.
Specifically, the image pickup device scans a barcode of the first order to obtain data information corresponding to the barcode, when the data information is not unique, that is, first data and second data exist, a first check instruction is obtained, the data is checked according to the first check instruction, whether the data has certain similarity or not is judged, order information is checked according to the data, and the nature of the data is determined, for example, the data may be the same data, that is, caused by too many copies, only one piece of data is reserved at the time, and the other piece of data is deleted; the data may be history data and latest data, and at this time, the history data is replaced with the latest data, and the latest data is used as order data.
Further, the verifying the first data and the second data according to the first verifying instruction, in step S140 of this embodiment of the present application, further includes:
step S141: obtaining revision time information of the first data and the second data;
step S142: obtaining a first weight value according to the revision time information;
step S143: obtaining a data comparison result of the first data and the second data, and obtaining a second weight value according to the comparison result;
step S144: performing weighted calculation on the first data and the second data according to the first weight value and the second weight value;
step S145: and comparing the first data and the second data subjected to weighting calculation to obtain a first verification result.
Specifically, the method for verifying the data according to the first verification instruction includes obtaining modification time information of second data of the first data, generating a first weight value according to the modification time information, obtaining a second weight value according to a data comparison result obtained by comparing contents of the first data and the second data, and performing weighted calculation on the first data and the second data according to the first weight value and the second weight value to obtain a first verification result. For example, when the modification time of the first data is earlier than that of the second data, the weight ratio of the first data and the weight ratio of the second data related to the modification time are respectively obtained according to the difference of the modification time, the comparison is performed according to the content of the first data and the content of the second data, the weight ratio of the first data and the weight ratio of the second data are respectively obtained according to the difference of the content, and the first data and the second data are respectively subjected to weighted calculation according to the weight ratio to obtain the verification result. By means of checking the data, more accurate order data of the first order are obtained, and a foundation is laid for the subsequent rapid and accurate optimization processing of the order.
Further, the obtaining a first verification result and taking the first verification result as first order information, in step S150 of this embodiment of the present application, further includes:
step S151: acquiring second order information, third order information and Nth order information, wherein the order information is subjected to replacement processing, and N is a natural number greater than 1;
step S152: generating a first check code according to the first order information, wherein the first check code corresponds to the first order information one to one;
step S153: generating a second check code according to the second order information and the first check code, wherein the second check code corresponds to the second order information one by one, and by analogy, generating an Nth check code according to the Nth order information and the N-1 th check code;
step S154: and copying and storing the order information and the check code on M electronic devices, wherein M is a natural number greater than 1.
In particular, the blockchain technique, also referred to as a distributed ledger technique, is an emerging technique in which several computing devices participate in "accounting" together, and maintain a complete distributed database together. The blockchain technology has been widely used in many fields due to its characteristics of decentralization, transparency, participation of each computing device in database records, and rapid data synchronization between computing devices. Generating a first check code according to the first order information, wherein the first check code corresponds to the first order information one by one; generating a second check code according to the second order information and the first check code, wherein the second check code corresponds to the second order information one to one; by analogy, generating an Nth check code according to the Nth order information and the Nth-1 check code, wherein N is a natural number greater than 1, respectively copying and storing all the order information and the check code on M devices, wherein the first order information and the first check code are stored on one device as a first block, the second order information and the second check code are stored on one device as a second block, the Nth order information and the Nth check code are stored on one device as an Nth block, when the order information needs to be called, after receiving data stored by a previous node, each subsequent node stores the data after checking through a common identification mechanism, and each storage unit is connected in series through a hash function, so that the order information is not easy to lose and damage, and the order information is encrypted through logic of a block chain, the security of the order information is ensured.
Further, the obtaining a first output result of the first training model, where the first output result includes a first plate graph arrangement result, in step S900 according to this embodiment of the present application, further includes:
step S910: obtaining second machine information, and inputting the second machine information into the first training model as third input information;
step S920: obtaining a second output result of the first training model, wherein the second output result comprises a second plate graph arrangement result;
step S930: and taking the second plate figure arrangement result as an alternative result of the first order information.
Specifically, the second machine is a machine that can also process the first order, the second machine has a different specification from the first machine, the second machine obtains information about a processing area of the second machine, inputs the information about the second machine into the first training model, and obtains a second output result of the first training model, the second output result is an arrangement result of a plate figure included in the first order based on a second plate figure of the second machine, the arrangement result of the second plate figure is used as a candidate result of the information about the first order, and when the first machine is occupied, the arrangement result of the second plate figure is used for processing through the second machine. By obtaining the alternative result of the first order, the optimization processing of the order can be quickly and accurately tamped.
Further, the embodiment of the present application further includes:
step S1511: obtaining plate graphical information of the second order;
step S1512: inputting the plate graphical information of the second order as fourth input information into the first training model;
step S1513: and obtaining a third output result of the first training model, wherein the third output result comprises a third plate graph arrangement result.
Specifically, the second order is an order with a delivery date close to that of the first order and a date of obtaining the order, the specific situation can be adjusted according to the actual situation to obtain the plate graphic information of the second order, the plate graphic information of the second order is obtained to ensure that the working space of the machine is reasonably used, the plate graphic information of the second order is input into the first training model as fourth input information, a third output result of the first training model is obtained, the third output result includes an arrangement result of the third plate graphics, and the arrangement result includes an arrangement result of the plate graphics of the first order and the second order.
Further, the obtaining a third output result of the first training model, where the third output result includes a third widget graph arrangement result, step S1513 in this embodiment of the present application further includes:
step S15131: obtaining a first predetermined space saving threshold;
step S15132: obtaining the total space occupied by the first order and the second order for respectively arranging the plate graphs;
step S15133: judging whether the size of the occupied space of the third plate figure arrangement result compared with the total occupied space meets the first preset space saving threshold value or not;
step S15134: when satisfied, applying the third widget graphical arrangement result to the first order and the second order.
Specifically, the first preset space-saving threshold is a preset value of the space-saving threshold set according to the actual situation, the plates of the first order and the second order are combined and processed, the risk of mixing exists, and when the space-saving is small, the combination processing of the first order and the second order is not recommended. Obtaining the size of the total space occupied by the first order and the second order for the plate figure arrangement respectively, and counting the machine stations according to the size of the occupied total space to obtain the total number of the occupied machine stations and the vacant space of the machine stations; obtaining the number of machines occupied by a third plate figure arrangement result and the vacant space of the machines, comparing the two results, and applying the third plate figure arrangement result to the first order and the second order when the number of machines occupied by the third plate figure arrangement result is less than the number of machines occupied by the first order and the second order for carrying out the plate figure arrangement respectively; and when the number of occupied machines is the same, judging whether the size of the occupied space of the third plate figure arrangement result compared with the total occupied space meets the first preset space saving threshold value or not, and applying the third plate figure arrangement result to the first order and the second order when the size meets the first preset space saving threshold value. The plate graphs of the first order and the second order are combined, arranged and processed through the first training model, the number of machines for processing the first order and the second order is saved, order distribution is more suitable for machines, and the technical effect of improving processing efficiency is achieved.
To sum up, the order data layout optimization method and system provided by the embodiment of the application have the following technical effects:
1. the first order information is obtained through the first camera device, the order data is classified and optimized according to first preset classification information, the plate graphic information of the first order is obtained according to the optimized first optimization result and is used as first input information, the first machine station information is used as second input information, the first input information and the second input information are input into a first training model, the first plate graphic arrangement result is obtained based on the characteristic that the training model continuously corrects and adjusts by self, the first order information is replaced by the first optimization result and the first plate graphic arrangement result, the data meeting the first preset classification and the optimization result of the plate graphic suitable for machine station processing are obtained through the typesetting of the order and the rapid optimization processing of the plate graphic of the order, and the order distribution is more suitable for the machine station, the technical effect of improving the processing efficiency is achieved.
2. Due to the fact that the data are verified, more accurate order data of the first order are obtained, and a foundation is laid for the follow-up rapid and accurate optimization processing of the order.
3. Because the mode of serially connecting each storage unit through the hash function is adopted, the order information is not easy to lose and damage, and the order information is encrypted through the logic of the block chain, so that the safety of the order information is ensured.
4. Due to the adoption of the mode of obtaining the alternative result of the first order, the optimization processing of the order can be quickly and accurately tamped for the follow-up.
5. Due to the fact that the mode that the plate graphs of the first order and the second order are combined, arranged and processed through the first training model is adopted, the number of machines for processing the first order and the second order is saved, order distribution is more suitable for machines, and the technical effect of improving processing efficiency is achieved.
Example two
Based on the same inventive concept as the order data layout optimization method in the foregoing embodiment, the present invention further provides an order data layout optimization system, as shown in fig. 2, the system includes:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain first order information through a first imaging device;
a second obtaining unit 12, where the second obtaining unit 12 is configured to obtain first preset classification information;
the first judging unit 13 is configured to judge whether the first order information is complete according to the first preset classification information;
a third obtaining unit 14, where the third obtaining unit 14 is configured to obtain a first classification optimization instruction when the first order information is complete;
a fourth obtaining unit 15, where the fourth obtaining unit 15 is configured to obtain a first optimization result of the first order according to the first classification optimization instruction through the first preset classification information;
a fifth obtaining unit 16, where the fifth obtaining unit 16 is configured to obtain the plate graphical information of the first order according to the first optimization result, and use the plate graphical information as first input information;
a sixth obtaining unit 17, where the sixth obtaining unit 17 is configured to obtain first station information according to the first order information, and use the first station information as second input information;
a first input unit 18, where the first input unit 18 is configured to input the first input information and the second input information into a first training model, where the first training model is obtained by training multiple sets of training data, and each of the multiple sets of training data includes: the first input information, the second input information and the identification information for identifying the plate figure arrangement result;
a seventh obtaining unit 19, where the seventh obtaining unit 19 is configured to obtain a first output result of the first training model, and the first output result includes a first plate graph arrangement result;
an eighth obtaining unit 20, where the eighth obtaining unit 20 is configured to obtain a first replacement instruction, and replace the first order information with the first optimization result and the first plate graph arrangement result according to the first replacement instruction.
Further, the system further comprises:
a ninth obtaining unit, configured to obtain first data of a first order through the first order information;
a second judging unit, configured to judge whether second data exists in the first order information;
a tenth obtaining unit, configured to obtain, when present, the first check instruction;
the first checking unit is used for checking the first data and the second data according to the first checking instruction;
an eleventh obtaining unit, configured to obtain a first verification result, where the first verification result is used as the first order information.
Further, the system further comprises:
a twelfth obtaining unit configured to obtain revision time information of the first data and the second data;
a thirteenth obtaining unit configured to obtain a first weight value according to the revision time information;
a fourteenth obtaining unit, configured to obtain a data comparison result of the first data and the second data, and obtain a second weight value according to the comparison result;
a fifteenth obtaining unit, configured to perform weighted calculation on the first data and the second data according to the first weight value and the second weight value;
a sixteenth obtaining unit, configured to compare the first data and the second data subjected to the weighting calculation, and obtain a first verification result.
Further, the system further comprises:
a seventeenth obtaining unit, configured to obtain second order information, third order information, and up to nth order information, where the order information is subjected to replacement processing, and N is a natural number greater than 1;
an eighteenth obtaining unit, configured to generate a first check code according to the first order information, where the first check code corresponds to the first order information one to one;
a nineteenth obtaining unit, configured to generate a second check code according to the second order information and the first check code, where the second check code corresponds to the second order information one to one, and by analogy, an nth check code is generated according to the nth order information and the nth-1 check code;
the first storage unit is used for copying and storing the order information and the check code on M pieces of electronic equipment, and M is a natural number greater than 1.
Further, the system further comprises:
a twentieth obtaining unit, configured to obtain second machine information, and input the second machine information as third input information to the first training model;
a twenty-first obtaining unit, configured to obtain a second output result of the first training model, where the second output result includes a second plate graph arrangement result;
a twenty-second obtaining unit, configured to use the second panel graph arrangement result as an alternative result of the first order information.
Further, the system further comprises:
a twenty-third obtaining unit configured to obtain panel figure information of the second order;
the second input unit is used for inputting the plate graphic information of the second order as fourth input information into the first training model;
a twenty-fourth obtaining unit, configured to obtain a third output result of the first training model, where the third output result includes a third widget graphical arrangement result.
Further, the system further comprises:
a twenty-fifth obtaining unit for obtaining a first predetermined space saving threshold;
a twenty-sixth obtaining unit, configured to obtain a total space occupied by the first order and the second order for respectively performing the graphic arrangement of the plates;
a third judging unit, configured to judge whether a size of an occupied space of the third widget graphic arrangement result compared to the total occupied space satisfies the first predetermined space saving threshold;
a first application unit to apply the third widget graphical arrangement result to the first order and the second order when satisfied.
Various changes and specific examples of the order data layout optimization method in the first embodiment of fig. 1 are also applicable to the order data layout optimization system in the present embodiment, and through the foregoing detailed description of the order data layout optimization method, those skilled in the art can clearly know the implementation method of the order data layout optimization system in the present embodiment, so for the brevity of the description, detailed descriptions are omitted here.
Exemplary electronic device
The electronic device of the embodiment of the present application is described below with reference to fig. 3.
Fig. 3 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
Based on the inventive concept of the order data layout optimization method in the foregoing embodiment, the present invention further provides an order data layout optimization system, on which a computer program is stored, which when executed by a processor implements the steps of any one of the foregoing order data layout optimization methods.
Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 306 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other systems over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
The method for optimizing the layout of the order data is applied to a furniture order data processing system, wherein the furniture order data processing system comprises a first camera device, and the method comprises the following steps: acquiring first order information through the first camera device; obtaining first preset classification information; judging whether the first order information is complete or not according to the first preset classification information; when the first order information is complete, obtaining a first classification optimization instruction; according to the first classification optimization instruction, obtaining a first optimization result of the first order through the first preset classification information; obtaining plate graphical information of the first order according to the first optimization result, and taking the plate graphical information as first input information; obtaining first machine information according to the first order information, and taking the first machine information as second input information; inputting the first input information and the second input information into a first training model, wherein the first training model is obtained by training a plurality of groups of training data, and each group of the plurality of groups of training data comprises: the first input information, the second input information and the identification information for identifying the plate figure arrangement result; obtaining a first output result of the first training model, wherein the first output result comprises a first plate graph arrangement result; and obtaining a first replacement instruction, and replacing the first order information with the first optimization result and the first plate figure arrangement result according to the first replacement instruction. The technical problems that in the prior art, the order typesetting optimization is inaccurate, the efficiency is low, and the optimized order cannot be matched with the machine more are solved, so that the order can be accurately and quickly optimized according to the order content, the order distribution is more suitable for the machine, and the technical effect of improving the processing efficiency is achieved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, 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 a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (9)
1. An order data layout optimization method is applied to a furniture order data processing system, wherein the furniture order data processing system comprises a first camera device, and the method comprises the following steps:
acquiring first order information through the first camera device;
obtaining first preset classification information;
judging whether the first order information is complete or not according to the first preset classification information;
when the first order information is complete, obtaining a first classification optimization instruction;
according to the first classification optimization instruction, obtaining a first optimization result of the first order through the first preset classification information;
obtaining plate graphical information of the first order according to the first optimization result, and taking the plate graphical information as first input information;
obtaining first machine information according to the first order information, and taking the first machine information as second input information;
inputting the first input information and the second input information into a first training model, wherein the first training model is obtained by training a plurality of groups of training data, and each group of the plurality of groups of training data comprises: the first input information, the second input information and the identification information for identifying the plate figure arrangement result;
obtaining a first output result of the first training model, wherein the first output result comprises a first plate graph arrangement result;
and obtaining a first replacement instruction, and replacing the first order information with the first optimization result and the first plate figure arrangement result according to the first replacement instruction.
2. The method of claim 1, further comprising:
obtaining first data of a first order through the first order information;
judging whether the first order information has second data or not;
when the first check instruction exists, obtaining a first check instruction;
according to the first checking instruction, checking the first data and the second data;
and obtaining a first verification result, and taking the first verification result as first order information.
3. The method of claim 2, wherein the first and second data are verified according to the first verification instruction, the method comprising:
obtaining revision time information of the first data and the second data;
obtaining a first weight value according to the revision time information;
obtaining a data comparison result of the first data and the second data, and obtaining a second weight value according to the comparison result;
performing weighted calculation on the first data and the second data according to the first weight value and the second weight value;
and comparing the first data and the second data subjected to weighting calculation to obtain a first verification result.
4. The method of claim 3, wherein the obtaining a first verification result, the first verification result being used as first order information, the method comprising:
acquiring second order information, third order information and Nth order information, wherein the order information is subjected to replacement processing, and N is a natural number greater than 1;
generating a first check code according to the first order information, wherein the first check code corresponds to the first order information one to one;
generating a second check code according to the second order information and the first check code, wherein the second check code corresponds to the second order information one by one, and by analogy, generating an Nth check code according to the Nth order information and the N-1 th check code;
and copying and storing the order information and the check code on M electronic devices, wherein M is a natural number greater than 1.
5. The method of claim 1, wherein said obtaining a first output of said first training model, said first output comprising a first panel graphical arrangement, comprises:
obtaining second machine information, and inputting the second machine information into the first training model as third input information;
obtaining a second output result of the first training model, wherein the second output result comprises a second plate graph arrangement result;
and taking the second plate figure arrangement result as an alternative result of the first order information.
6. The method of claim 4, wherein the method further comprises:
obtaining plate graphical information of the second order;
inputting the plate graphical information of the second order as fourth input information into the first training model;
and obtaining a third output result of the first training model, wherein the third output result comprises a third plate graph arrangement result.
7. The method of claim 6, wherein the obtaining a third output of the first training model, the third output comprising a third widget graphical arrangement, the method further comprises:
obtaining a first predetermined space saving threshold;
obtaining the total space occupied by the first order and the second order for respectively arranging the plate graphs;
judging whether the size of the occupied space of the third plate figure arrangement result compared with the total occupied space meets the first preset space saving threshold value or not;
when satisfied, applying the third widget graphical arrangement result to the first order and the second order.
8. An order data layout optimization system, wherein the system comprises:
the first obtaining unit is used for obtaining first order information through a first camera device;
a second obtaining unit, configured to obtain first preset classification information;
the first judging unit is used for judging whether the first order information is complete or not through the first preset classification information;
a third obtaining unit, configured to obtain a first classification optimization instruction when the first order information is complete;
a fourth obtaining unit, configured to obtain, according to the first classification optimization instruction, a first optimization result of the first order according to the first preset classification information;
a fifth obtaining unit, configured to obtain, according to the first optimization result, plate graphical information of the first order, and use the plate graphical information as first input information;
a sixth obtaining unit, configured to obtain first station information according to the first order information, and use the first station information as second input information;
a first input unit, configured to input the first input information and the second input information into a first training model, where the first training model is obtained by training multiple sets of training data, and each of the multiple sets of training data includes: the first input information, the second input information and the identification information for identifying the plate figure arrangement result;
a seventh obtaining unit, configured to obtain a first output result of the first training model, where the first output result includes a first plate graph arrangement result;
and the eighth obtaining unit is used for obtaining a first replacing instruction and replacing the first order information with the first optimization result and the first plate figure arrangement result according to the first replacing instruction.
9. An order data layout optimization system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the steps of the method of any one of claims 1 to 7 are implemented when the program is executed by the processor.
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Cited By (1)
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| CN116882555A (en) * | 2023-06-26 | 2023-10-13 | 广东工业大学 | Multi-order layout optimization method with limited sorting stations |
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