Intelligent board splicing and order finding method and device for PCBs

Abstract

The invention provides an intelligent board splicing and order finding method and device for PCBs, and the method comprises the following steps: obtaining a plurality of PCB production orders, and enabling each PCB production order to comprise a corresponding board splicing parameter; carrying out board splicing according to the board splicing parameters of each PCB production order, and obtaining a plurality of work orders based on a board splicing result; the method comprises the steps of obtaining a PCB production order, obtaining a PCB simulation image corresponding to each PCB production order, obtaining a PCB physical image of each executed work order after the work order is executed, obtaining the PCB production order corresponding to the executed work order based on the image similarity between the PCB physical image and each PCB simulation image, and packaging and delivering after all work orders under the PCB production order are executed. According to the scheme, the PCB production orders are allocated to different work orders for processing in the board splicing process, so that the PCB substrate and the utilization rate are greatly improved.

Description

Technical Field

[0001] The present application relates to the field of PCB board manufacturing technology, and in particular to a method and device for intelligent panel assembly and order finding of PCB boards. Background Art

[0002] In the field of PCB board manufacturing technology, with the vigorous development of the electronics industry, the market demand for printed circuit boards (PCBs) is growing and showing a diversified trend.

[0003] Currently, the PCB industry widely uses panelization technology to process customer orders to improve production efficiency. Specifically, based on information such as the PCB's shape, size, and quantity, a specific algorithm is used to generate a panelization plan, which then produces and delivers the PCBs that meet the customer's needs. For example, invention application number 201510163601.9 utilizes a PCB substrate that matches the shape, size, and other parameters of the PCB to be produced. This type of panelization technology has demonstrated certain feasibility and effectiveness in handling ordinary, routine orders.

[0004] However, existing technologies have significant limitations. Constrained by traditional processes, a customer order is typically completed within a single work order. This makes it difficult to flexibly adjust panelization strategies during production when encountering unusual parameters such as order quantity and size. For example, if there are orders with a small number of large sizes, or a large number of orders with widely varying sizes, panelization according to the existing model will result in a significant amount of space on the PCB substrate being unused, resulting in low overall PCB substrate utilization. This not only increases production costs for companies and wastes resources, but also impacts the production efficiency and competitiveness of the entire electronics industry. Summary of the Invention

[0005] The embodiment of the present application provides a method and device for intelligent panelization and order finding of PCB boards, which allocates PCB production orders to different work orders for processing during the panelization process, thereby greatly improving the PCB substrate and utilization rate.

[0006] In a first aspect, an embodiment of the present application provides a method for intelligent panelization and order finding of PCB boards, the method comprising:

[0007] Acquire multiple PCB production orders, each of the PCB production orders including corresponding panelization parameters, wherein the panelization parameters include a total number of PCB boards to be produced and parameters of the PCB boards to be produced;

[0008] Panelization is performed according to the panelization parameters of multiple PCB production orders, and multiple work orders are obtained based on the panelization results. During the panelization process, one PCB production order can be split into different work orders according to the panelization results;

[0009] Get the PCB simulation image corresponding to each PCB production order. When the work order is completed, get the physical image of each completed work order. Based on the image similarity between the physical PCB image and each PCB simulation image, get the PCB production order corresponding to the completed work order. When all work orders under the PCB production order are completed, pack and ship them.

[0010] In a second aspect, an embodiment of the present application provides an intelligent PCB board assembly and order finding device, comprising:

[0011] An acquisition module is configured to acquire a plurality of PCB production orders, each of which includes corresponding panelization parameters, wherein the panelization parameters include a total number of PCB boards to be produced and parameters of the PCB boards to be produced;

[0012] The panelization module performs panelization according to the panelization parameters of multiple PCB production orders and obtains multiple work orders based on the panelization results. During the panelization process, a PCB production order can be split into different work orders based on the panelization results;

[0013] The shipping module is used to obtain the PCB simulation image corresponding to each PCB production order. When the work order is completed, the physical image of the PCB of each completed work order is obtained. Based on the image similarity between the physical PCB image and each PCB simulation image, the PCB production order corresponding to the completed work order is obtained. When all work orders under the PCB production order are completed, they are packaged and shipped.

[0014] In a third aspect, an embodiment of the present application provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute a method for intelligent panelization and order finding of PCB boards.

[0015] In a fourth aspect, an embodiment of the present application provides a readable storage medium, in which a computer program is stored. The computer program includes a program code for controlling a process to execute a process, and the process includes a method for intelligent panelization and order finding of PCB boards.

[0016] The main contributions and innovations of the present invention are as follows:

[0017] In the panelization process, the embodiment of the present application splits the PCB production order into different work orders for processing, thereby splitting orders with relatively abnormal or small quantities into reasonable quantities and then performing panelization, which greatly improves the utilization rate of PCB substrates, saves board materials, and enhances corporate profits and competitiveness in the electronics industry; the embodiment of the present application extracts the vector of the PCB physical image based on the deep learning CNN algorithm, and then uses the similarity measurement algorithm to find the feature vector that is most similar to the PCB simulation image in the database, thereby finding the execution work order corresponding to the PCB production order, and can quickly merge the split orders to ensure the quantity of finished products shipped to customers without increasing logistics costs.

[0018] The details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0020] Figure 1 This is a flow chart of a method for intelligent panelization and order finding of PCB boards according to an embodiment of the present application;

[0021] Figure 2 This is a schematic diagram of a process for panelizing a PCB production order according to an embodiment of the present application;

[0022] Figure 3 This is a logical flow chart for obtaining and executing PCB production orders corresponding to completed orders according to an embodiment of the present application.

[0023] Figure 4 This is a structural block diagram of a device for intelligent PCB board assembly and order finding according to an embodiment of the present application;

[0024] Figure 5 Schematic diagram of the hardware structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The implementations described in the following exemplary embodiments are not intended to represent all implementations consistent with one or more embodiments of this specification. Rather, they are merely examples of apparatuses and methods consistent with certain aspects of one or more embodiments of this specification, as detailed in the appended claims.

[0026] It should be noted that in other embodiments, the steps of the corresponding method are not necessarily performed in the order shown and described in this specification. In some other embodiments, the method may include more or fewer steps than those described in this specification. In addition, a single step described in this specification may be broken down into multiple steps for description in other embodiments, and multiple steps described in this specification may be combined into a single step for description in other embodiments.

[0027] Example 1

[0028] The embodiment of the present application provides a method for intelligent panelization and order finding of PCB boards, which allocates PCB production orders to different work orders for processing during the panelization process, thereby greatly improving the utilization rate of PCB substrates. Specifically, referring to Figure 1 , the method comprising:

[0029] Acquire multiple PCB production orders, each of the PCB production orders including corresponding panelization parameters, wherein the panelization parameters include a total number of PCB boards to be produced and parameters of the PCB boards to be produced;

[0030] Panelization is performed according to panelization parameters of multiple PCB production orders, and multiple work orders are obtained based on the panelization results. During the panelization process, a PCB production order can be split into different work orders according to the panelization results, and the corresponding relationship between the PCB production order and the work order is saved in the database management system;

[0031] Get the PCB simulation image corresponding to each PCB production order. When the work order is completed, get the physical image of each completed work order. Based on the image similarity between the physical PCB image and each PCB simulation image, get the PCB production order corresponding to the completed work order. When all work orders under the PCB production order are completed, pack and ship them.

[0032] In some specific embodiments, the existing PCB panelization can only be completed through one work order for one order. For example, among multiple PCB production orders, there are a large number of orders with demand quantities of 3 and 5, but there is an order with a demand quantity of 8. If the order with quantity 8 is not split, then the production combination, whether it is combined with the order with quantity 3 or 5, needs to increase the quantity. For example, the combination with the order with quantity 3 needs to increase the quantity to 9 to make it into 3 panels, and the combination with quantity 5 needs to increase the quantity to 10, which increases the cost of production. However, when 8 is split into 3+5, 3 is combined with the order with quantity 3, and 5 is combined with the order with quantity 5, so there is no need to increase the additional quantity, which improves the utilization rate of PCB panels and reduces costs.

[0033] In the PCB production business process, companies will obtain PCB production orders through various channels. The PCB production orders will clearly specify the total number of PCB boards to be produced and the parameters of the PCB boards to be produced required by the customer. Among them, the parameters of the PCB boards to be produced include the size and circuit layout information of the PCB boards to be produced.

[0034] Specifically, the dimensions of the PCB to be produced are the dimensional specifications of the PCB to be produced, accurate to specific values such as length, width, and thickness. This determines the size of the raw materials and the parameters of the processing equipment required during the production process. The circuit layout information of the PCB to be produced, including the number of circuit layers, line width, line spacing, etc., is directly related to the complexity and technical requirements of the production process.

[0035] In addition, for some complex PCB production orders, the parameters of the PCB boards to be produced also include aperture size, distribution, and surface treatment process requirements. Specifically, different apertures on the PCB board are used to install different electronic components, which have specific requirements for the drilling process. Therefore, in specific scenarios, there are specific requirements for aperture size and distribution. The surface treatment process requirements are tin spraying, gold immersion, or other treatment methods, which affect the surface performance and final use of the PCB board.

[0036] In some specific embodiments, the present solution adopts any conventional panelization algorithm for panelization. It is worth mentioning that the panelization algorithm of the present solution can allocate any PCB order to different work orders for execution, thereby greatly reducing the waste of PCB boards.

[0037] For example, there are multiple PCB production orders order1, order2, order3, order4, order5 and order6. The total number of PCB boards to be produced in order1 and order2 is 25, and the total number of PCB boards to be produced in order4, order5 and order6 is 50. However, the total number of PCB boards to be produced in order3 is 75. When assembling orders, the total number of PCB boards to be produced in order3 can be split into 25+50 for paneling. The process diagram for paneling PCB production orders is shown as follows: Figure 2 shown.

[0038] In some specific embodiments, PCB engineering data of a PCB production order is obtained, and a pre-trained image generation algorithm is used to generate a PCB simulation image based on the PCB engineering data.

[0039] Specifically, the PCB engineering data is a gerber file. By parsing the gerber file and using a pre-trained image generation algorithm, a simulation image corresponding to the PCB production order can be generated based on the gerber file.

[0040] In some specific embodiments, the present solution uses a camera to obtain a physical image of a PCB. When comparing the physical image of the PCB with each simulated image of the PCB for image similarity, feature extraction is performed on the simulated image of the PCB to obtain a PCB simulation feature vector. Feature extraction is performed on the physical image of the PCB to obtain a physical PCB feature vector. The PCB production order corresponding to the PCB simulation vector having the highest similarity to the physical PCB feature vector is selected as the PCB production order corresponding to the executed order.

[0041] Furthermore, the vector similarity between the PCB simulation feature vector and the PCB physical feature vector is calculated using a cosine similarity algorithm.

[0042] Specifically, the logic flow chart of the PCB production order corresponding to the completed order is obtained as follows: Figure 3 As shown in the figure, in this solution, CNN deep learning algorithm is used to extract features of PCB simulation images and PCB real images.

[0043] In other words, this solution uses a deep learning CNN algorithm to extract dimensional features from images. It then uses a similarity metric to find the feature vector most similar to the database, thereby obtaining the corresponding work order number and completing the order search process. This allows for the rapid consolidation of split orders, ensuring the number of finished products delivered to customers without increasing logistics costs.

[0044] Example 2

[0045] Based on the same concept, refer to Figure 4 This application also proposes a smart PCB board assembly and order-finding device, including:

[0046] An acquisition module is configured to acquire a plurality of PCB production orders, each of which includes corresponding panelization parameters, wherein the panelization parameters include a total number of PCB boards to be produced and parameters of the PCB boards to be produced;

[0047] The panelization module performs panelization according to the panelization parameters of multiple PCB production orders and obtains multiple work orders based on the panelization results. During the panelization process, a PCB production order can be split into different work orders based on the panelization results;

[0048] The shipping module is used to obtain the PCB simulation image corresponding to each PCB production order. When the work order is completed, the physical image of the PCB of each completed work order is obtained. Based on the image similarity between the physical PCB image and each PCB simulation image, the PCB production order corresponding to the completed work order is obtained. When all work orders under the PCB production order are completed, they are packaged and shipped.

[0049] Example 3

[0050] This embodiment also provides an electronic device, referring to Figure 5 , includes a memory 404 and a processor 402, wherein the memory 404 stores a computer program, and the processor 402 is configured to run the computer program to perform the steps in any of the above method embodiments.

[0051] Specifically, the processor 402 may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0052] Among them, the memory 404 may include a large-capacity memory 404 for data or instructions. By way of example and not limitation, the memory 404 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 404 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 404 may be inside or outside the data processing device. In a specific embodiment, the memory 404 is a non-volatile memory. In a specific embodiment, the memory 404 includes a read-only memory (ROM) and a random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (Programmable Read-Only Memory, abbreviated as PROM), an erasable PROM (Erasable Programmable Read-Only Memory, abbreviated as EPROM), an electrically erasable PROM (Electrically Erasable Programmable Read-Only Memory, abbreviated as EEPROM), an electrically alterable ROM (Electrically Alterable Read-Only Memory, abbreviated as EAROM) or a flash memory (FLASH) or a combination of two or more of these. In appropriate circumstances, the RAM can be a static random access memory (SRAM) or a dynamic random access memory (DRAM), wherein the DRAM can be a fast page mode dynamic random access memory 404 (FPMDRAM), an extended data output dynamic random access memory (EDODRAM), a synchronous dynamic random access memory (SDRAM), etc.

[0053] The memory 404 may be used to store or cache various data files required for processing and / or communication, as well as possible computer program instructions executed by the processor 402 .

[0054] The processor 402 reads and executes computer program instructions stored in the memory 404 to implement any one of the intelligent PCB board assembly and order finding methods in the above embodiments.

[0055] Optionally, the electronic device may further include a transmission device 406 and an input / output device 408 , wherein the transmission device 406 is connected to the processor 402 , and the input / output device 408 is connected to the processor 402 .

[0056] Transmission device 406 can be used to receive or send data via a network. Specific examples of the aforementioned network may include a wired or wireless network provided by a communications provider of the electronic device. In one embodiment, the transmission device includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In one embodiment, transmission device 406 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0057] The input / output device 408 is used to input or output information. In this embodiment, the input information may be a PCB production order, parameters of the PCB to be produced, etc., and the output information may be a corresponding execution work order, etc.

[0058] Optionally, in this embodiment, the processor 402 may be configured to execute the following steps through a computer program:

[0059] Acquire multiple PCB production orders, each of the PCB production orders including corresponding panelization parameters, wherein the panelization parameters include a total number of PCB boards to be produced and parameters of the PCB boards to be produced;

[0060] Panelization is performed according to the panelization parameters of multiple PCB production orders, and multiple work orders are obtained based on the panelization results. During the panelization process, one PCB production order can be split into different work orders according to the panelization results;

[0061] Get the PCB simulation image corresponding to each PCB production order. When the work order is completed, get the physical image of each completed work order. Based on the image similarity between the physical PCB image and each PCB simulation image, get the PCB production order corresponding to the completed work order. When all work orders under the PCB production order are completed, pack and ship them.

[0062] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be repeated here.

[0063] In general, various embodiments may be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. Some aspects of the invention may be implemented in hardware, while other aspects may be implemented in firmware or software executed by a controller, microprocessor, or other computing device, but the invention is not limited thereto. Although various aspects of the invention may be shown and described as block diagrams, flow charts, or using some other graphical representation, it should be understood that, as non-limiting examples, the blocks, devices, systems, techniques, or methods described herein may be implemented in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or a controller or other computing device, or some combination thereof.

[0064] The embodiments of the present invention may be implemented by computer software that is executable by a data processor of a mobile device, such as in a processor entity, or by hardware, or by a combination of software and hardware. Computer software or programs (also referred to as program products) including software routines, applets and / or macros may be stored in any device-readable data storage medium, and they include program instructions for performing specific tasks. A computer program product may include one or more computer executable components that are configured to perform an embodiment when the program is run. One or more computer executable components may be at least one software code or a portion thereof. In addition, it should be noted at this point that, for example, Figure 5 Any block of the logic flow in the program may represent program steps, or interconnected logic circuits, blocks and functions, or a combination of program steps and logic circuits, blocks and functions. The software may be stored on physical media such as memory chips or memory blocks implemented within the processor, magnetic media such as hard disks or floppy disks, and optical media such as, for example, DVDs and their data variants, CDs, etc. Physical media are non-transitory media.

[0065] Those skilled in the art should understand that the technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0066] The above embodiments merely illustrate several embodiments of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for intelligent PCB board assembly and order finding, characterized in that: The following steps are involved: Acquire multiple PCB production orders, each of the PCB production orders including corresponding panelization parameters, wherein the panelization parameters include a total number of PCB boards to be produced and parameters of the PCB boards to be produced; Panelization is performed according to the panelization parameters of multiple PCB production orders, and multiple work orders are obtained based on the panelization results. During the panelization process, one PCB production order can be split into different work orders according to the panelization results; Get the PCB simulation image corresponding to each PCB production order. When the work order is completed, get the physical image of each completed work order. Based on the image similarity between the physical PCB image and each PCB simulation image, get the PCB production order corresponding to the completed work order. When all work orders under the PCB production order are completed, pack and ship them.

2. The method for intelligent PCB board assembly and order finding according to claim 1, characterized in that: The parameters of the PCB board to be produced include the size and circuit layout information of the PCB board to be produced.

3. The intelligent PCB board assembly and order finding method according to claim 1, characterized in that: By obtaining the PCB engineering data of the PCB production order and using the pre-trained image generation algorithm to generate a PCB simulation image based on the PCB engineering data.

4. The intelligent PCB board assembly and order finding method according to claim 1, characterized in that: A physical image of a PCB is acquired through a camera. When comparing the physical image of the PCB with each simulated image for image similarity, feature extraction is performed on the simulated image of the PCB to obtain a PCB simulation feature vector. Feature extraction is also performed on the physical image of the PCB to obtain a physical PCB feature vector. A PCB production order corresponding to the PCB simulation vector having the highest similarity to the physical PCB feature vector is selected as the PCB production order corresponding to the completed work order.

5. The intelligent PCB board assembly and order finding method according to claim 4, characterized in that: The vector similarity between the PCB simulation feature vector and the PCB physical feature vector is calculated using a similarity measurement algorithm.

6. A smart PCB board assembly and order finding device, characterized in that: include: An acquisition module is configured to acquire a plurality of PCB production orders, each of which includes corresponding panelization parameters, wherein the panelization parameters include a total number of PCB boards to be produced and parameters of the PCB boards to be produced; The panelization module performs panelization according to the panelization parameters of multiple PCB production orders and obtains multiple work orders based on the panelization results. During the panelization process, a PCB production order can be split into different work orders based on the panelization results; The shipping module is used to obtain the PCB simulation image corresponding to each PCB production order. When the work order is completed, the physical image of the PCB of each completed work order is obtained. Based on the image similarity between the physical PCB image and each PCB simulation image, the PCB production order corresponding to the completed work order is obtained. When all work orders under the PCB production order are completed, they are packaged and shipped.

7. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the intelligent panelization and order finding method for PCB boards described in any one of claims 1-5.

8. A readable storage medium, characterized in that: The readable storage medium stores a computer program, which includes a program code for controlling a process to execute a process, and the process includes a smart panelization and order finding method for PCB boards according to any one of claims 1-5.

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