A SMT intelligent process optimization control method

Abstract

The embodiment of this specification discloses an SMT intelligent process optimization control method, characterized in that the method includes: a data acquisition system collects product defect data produced during the detection process; calling an expert system to perform process analysis on the product defect data to obtain equipment adjustment parameters; and controlling the manufacturing execution system according to the equipment adjustment parameters to improve product defects. The present invention can improve the rapid response capability of the SMT process during the introduction of new products, make the SMT mounting production line have stronger product adaptability, and meet the needs of different products for different process processes.

Description

Technical Field

[0001] The present application relates to the field of surface mounting technology, and in particular to a SMT intelligent process optimization control method. Background Art

[0002] Automatic optimization and control of the process during SMT trial production, that is, online intelligentization of SMT production process.

[0003] As the speed of electronic product replacement accelerates, the market characteristics of newer, faster, more varieties and smaller batches are becoming more apparent. How to speed up the matching of the industrial chain, increase the speed of supply, shorten the product development cycle, reduce the time to market, and enhance the ability of new technology products to quickly respond to market changes will become the primary issue facing the future development of the electronic manufacturing industry.

[0004] Due to the influence of the new product's own characteristics and design for manufacturability (DFM) capabilities, the process is uncertain. A large number of professional and technical personnel are required before and after the SMT mounting process. It takes a long time and a lot of energy to design, optimize, adjust and improve the new product process. Only after repeated verification by technical personnel can the stability of the final mounting process be ensured, so that the reliability of the product is guaranteed. Summary of the invention

[0005] In view of this, an embodiment of the present application provides an SMT intelligent process optimization control method for solving the problem that due to the uncertainty of the production process of new products, a large amount of manpower and time are invested in unresolved process problems during the process, resulting in increased production costs and delays in product research and development and trial production cycles.

[0006] To solve the above technical problems, the embodiments of this specification are implemented as follows:

[0007] A SMT intelligent process optimization control method, the method comprising:

[0008] The data collection system collects product defect data produced during the inspection process;

[0009] Calling an expert system to perform process analysis on the product defect data to obtain equipment adjustment parameters;

[0010] The manufacturing execution system is controlled according to the equipment adjustment parameters to improve product defects.

[0011] Optionally, the data collection system collects product defect data produced during the inspection process, specifically including:

[0012] After the PCB printed circuit board is screen-printed with solder paste by the screen printer, the screen printing is tested with a solder paste thickness tester to obtain product defect data;

[0013] The calling of the expert system to perform process analysis on the product defect data to obtain equipment adjustment parameters specifically includes:

[0014] The product defect data is extracted to a computer-aided process design system through a data collector. The computer-aided process design system calls the knowledge base data in an expert system to analyze the product defect data and outputs device adjustment parameters through data comparison.

[0015] Optionally, the data acquisition system includes: a computer-aided process design system and a detection device, and the computer-aided process design system is connected to the detection device via a data acquisition device.

[0016] Optionally, the detection equipment includes: a solder paste thickness tester, an automatic optical detector and an X-ray detector.

[0017] Optionally, the manufacturing execution system includes: a silk screen printing device, a patch device and a reflow device.

[0018] Optionally, the solder paste thickness tester is used to detect the amount, thickness, offset and solder leakage of solder paste on each pad.

[0019] Optionally, there are two automatic optical detectors, which are used to detect the quality of the patch process and the reflow process respectively.

[0020] Optionally, the overall process of the SMT is: silk screen printing, solder paste thickness detection, patch, automatic optical detection, reflow, automatic optical detection and X-ray detection.

[0021] Optionally, when the X-ray detection finds that the original component has a cold solder joint, the equipment parameters of the silk screen printing or the reflow are adjusted.

[0022] Optionally, when the solder paste thickness detection finds defects in the original product, the equipment parameters of the silk screen or the patch are adjusted.

[0023] At least one of the above technical solutions adopted in the embodiments of this specification can achieve the following beneficial effects:

[0024] The present invention can improve the rapid response capability of the SMT process during the introduction of new products, so that the SMT mounting production line has stronger product adaptability and meets the needs of different products for different process steps. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] 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:

[0026] Figure 1 A schematic diagram of the flow chart of the SMT intelligent process optimization control method provided in the embodiments of this specification;

[0027] Figure 2 A flow chart of the intelligent process control process of the SMT intelligent process optimization control method provided in the embodiments of this specification. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0029] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0030] The Surface Mount Technology (SMT) intelligent online inspection system is a self-learning expert system specifically for SMT production. It can not only measure and control printing, patch and welding results with ultra-high precision, but also help technicians continuously optimize the SMT process to make it more stable and reliable. The system platform consists of two parts, one of which is a computer-aided process planning system (CAPP) that connects and collects data with solder paste thickness testers (SPI), automatic optical inspection instruments (AOI), and X-ray inspection instruments (AXI), and the other is a built-in expert system (ES), that is, an expert knowledge database. During production operations, CAPP can proactively and automatically control the connected screen printers, patch machines, and reflow ovens through the Manufacturing Execution System (MES), ensuring higher quality, higher production capacity, and higher production line efficiency. In terms of inspection equipment SPI and AOI, DLP chips and 8 million independently controlled micromirrors are used. By using a combination of 2D processes and advanced 3D measurement methods, it is possible to analyze solder conditions faster, more flexibly, and more accurately than traditional high-end SPI systems. In terms of digital inspection and analysis, the recorded measurement data is stored in the CAPP database. With the help of big data technology, it is not only possible to check the latest printing, patch, and soldering results in real time, but also to find potential improvements by viewing historical data and verifying the relationship between settings and results. In addition, because it is connected to the screen printer, patch machine, and reflow oven, it can actively control and optimize the entire equipment settings alone, making it more stable and reliable without human assistance.

[0031] Figure 1 The following is a flow chart of the SMT intelligent process optimization control method provided in the embodiments of this specification. Figure 1 As shown, the method includes:

[0032] Step 110: The data collection system collects product defect data produced during the inspection process;

[0033] Step 120: calling an expert system to perform process analysis on the product defect data to obtain equipment adjustment parameters;

[0034] Step 130: Control the manufacturing execution system according to the equipment adjustment parameters to improve product defects.

[0035] In one or more embodiments, the data collection system collects product defect data produced during the inspection process, which may specifically include:

[0036] After the PCB printed circuit board is screen-printed with solder paste by the screen printer, the screen printing is tested with a solder paste thickness tester (SPI) to obtain product defect data;

[0037] The calling of the expert system to perform process analysis on the product defect data to obtain equipment adjustment parameters specifically includes:

[0038] The product defect data is extracted to a computer-aided process design system (CAPP) through a data collector. The computer-aided process design system (CAPP) calls the knowledge base data in the expert system to analyze the product defect data and outputs equipment adjustment parameters through data comparison.

[0039] In one or more embodiments, the data acquisition system may include: a computer-aided process design system (CAPP) and a detection device, and the computer-aided process design system (CAPP) is connected to the detection device through a data acquisition device.

[0040] In one or more embodiments, the inspection equipment may include: a solder paste thickness tester (SPI), an automatic optical inspection instrument (AOI) and an X-ray inspection instrument (AXI).

[0041] In one or more embodiments, the manufacturing execution system may include: a screen printing device, a patch device, and a reflow device.

[0042] In one or more embodiments, the solder paste thickness tester (SPI) is used to detect the amount, thickness, offset and solder leakage of solder paste on each pad.

[0043] In one or more embodiments, there are two automatic optical inspection instruments (AOI), which are used to inspect the quality of the patch process and the reflow process respectively.

[0044] In one or more embodiments, the overall process of the SMT is: silk screen printing, solder paste thickness detection, patch, automatic optical inspection, reflow, automatic optical inspection and X-ray inspection.

[0045] In one or more embodiments, when the X-ray detection finds that the original component has a cold solder joint, the equipment parameters of the silk screen printing or the reflow are adjusted.

[0046] In one or more embodiments, when the solder paste thickness detection finds defects in the original product, the equipment parameters of the silk screen or the patch are adjusted.

[0047] This solution transforms the process research results and the experience accumulated in process design and control over the years into process design thinking and implants it into the computer-aided process compilation system CAPP to perform process modeling. Through MES, the data interface between the information system and the production equipment is opened up, and a linkage and coordinated control relationship is established between each relatively independent automation equipment, realizing linkage control between inspection equipment and production equipment.

[0048] The problem data discovered during inspection is transmitted back to the system for analysis. The system automatically makes judgments based on pre-set process solutions and transmits the control parameters used for improvement back to the corresponding production equipment for automatic adjustment and correction, thereby reducing human intervention in the process, achieving online intelligent detection of products in the production process, automatic adjustment and optimal control of process parameters, and improving the production line's ability to think independently and operate continuously.

[0049] This design is equivalent to adding a brain to the SMT production line. It can independently think and judge the defects generated during the production process, and control the equipment to improve the product itself without human intervention.

[0050] Figure 2 The following is a flow chart of the process intelligent control process of the SMT intelligent process optimization control method provided in the embodiments of this specification. Figure 2 As shown in the figure, the upper dotted box represents the information layer, that is, the system software part, and the lower dotted box represents the physical layer, that is, the SMT production inspection equipment. From silk screen printing to AXI is the entire process of product placement. The CAPP and MES in the middle realize the data collection and control of SMT equipment. The ES expert system is equivalent to the brain, analyzing the collected information and generating instructions to act on the equipment.

[0051] The execution process is shown in the figure above: the CAPP system is connected to AOI, SPI, AXI and other testing equipment through the data collector to collect product defect data produced during the testing process, and conducts process analysis on defects (i.e. what kind of defect data corresponds to what improvement parameters of what equipment) by calling the ES system knowledge base (converting the company's process experience into process control thinking for digital modeling and implanting it into the database), and outputs the obtained improvement instructions (i.e. equipment adjustment parameters) to the control layer of production equipment such as silk screen printing, patch, and reflow through the data interface between the MES system and the equipment, and adjusts and updates its control parameters to achieve the improvement effect. That is, the self-perception and self-adaptation of the SMT production line is realized - intelligent control of the SMT trial production process.

[0052] Process Description

[0053] 1. The PCB printed circuit board is screen printed with solder paste (the solder paste is printed on the pads of the PCB components).

[0054] 2. Enter the SPI solder paste detector (to detect the quality of solder paste printing, including the amount of solder paste on each pad, thickness, offset, tin leakage, etc.) for detection, and output the defect data found after the detection (originally displayed to the process personnel through the display, and the process personnel made a judgment, and then adjusted the relevant printing parameters of the screen printer to reach the state of good products. For example, if tin leakage occurs, according to process experience, it is necessary to reduce the demoulding speed of the screen printer and increase the scraper pressure. The process personnel need to adjust the relevant parameters on the screen printer to achieve the purpose of improvement; for example, if the solder paste of individual pads is offset, according to the size of the offset, the placement position of the component of the placement machine can be adjusted to align with the solder paste position instead of the pad position, and the state of good products after welding can be achieved. Otherwise, defects such as component suspension bridges and monuments will appear after welding.)

[0055] 3. The defect data output by SPI is extracted into the CAPP process control system through the data collector. The CAPP system calls the ES expert knowledge base data for analysis (the above process defect improvement analysis process is digitally modeled and stored in the database, that is, what defect parameters correspond to what improvement parameters of what equipment), outputs the improvement parameters through data comparison, and writes the improvement parameters into the equipment through the equipment data interface, which is used as a control instruction to control the equipment for adjustment.

[0056] Among them, SPI, AOI, and AXI are all detection equipment. Through CAPP and ES extraction and analysis, the improvement instructions are written into the silk screen, patch, and reflow production equipment.

[0057] In this process, each detection device can only detect the equipment of the previous process connected to it, which is a test and verification of the results of the previous process. However, the defects generated by this process may be related to multiple previous processes. For example, the final AXI test found that the component had a cold soldering defect, so the cold soldering may be related to the preheating parameters of the reflow process, the amount of solder paste adhesion in the silk screen process, etc. Although SPI only detects the silk screen process at the front end, the improvement method can be to adjust the parameters of the silk screen process or the parameters of the back-end patch process. For example, if the solder paste is offset in the silk screen process, the parameters of the silk screen process can be adjusted to make the solder paste align with the pad, or the parameters of the patch process can be changed to align the component with the solder paste position. For example, under normal conditions, the component needs to be aligned with the pad position. Due to the defect of solder paste offset, the component mounting position of the patch machine can be adjusted so that it is not aligned with the pad position, but aligned with the solder paste printing position, so that a good welding effect can be achieved after reflow.

[0058] In order to analyze defects and improve the process, this solution converts the existing operations that rely on the experience of production personnel into digital modeling. Based on the modeling, the process adjustment parameters are determined for any defect. Automatic analysis and improvement control are achieved by establishing a judgment and improvement rule database.

[0059] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A SMT intelligent process optimization control method, characterized in that: The method comprises: The data collection system collects product defect data produced during the inspection process; Calling an expert system to perform process analysis on the product defect data to obtain equipment adjustment parameters; Controlling the manufacturing execution system according to the equipment adjustment parameters to improve product defects; The data collection system collects product defect data produced during the inspection process, specifically including: After the PCB printed circuit board is screen-printed with solder paste by the screen printer, the screen printing is tested with a solder paste thickness tester to obtain product defect data; The calling of the expert system to perform process analysis on the product defect data to obtain equipment adjustment parameters specifically includes: Extract the product defect data to the computer-aided process design system through a data collector, the computer-aided process design system calls the knowledge base data in the expert system to analyze the product defect data, and outputs the device adjustment parameters through data comparison; The overall process of SMT is: screen printing, solder paste thickness detection, patch, automatic optical inspection, reflow, automatic optical inspection and X-ray inspection; When the X-ray detection finds that the original part is poorly soldered, adjusting the equipment parameters of the silk screen printing or the reflow; When the solder paste thickness detection finds defects in the original product, the equipment parameters of the silk screen printing or the patch are adjusted.

2. The control method according to claim 1, characterized in that: The data acquisition system comprises: a computer-aided process design system and a detection device, and the computer-aided process design system is connected with the detection device through a data acquisition device.

3. The control method according to claim 2, characterized in that: The detection equipment includes: a solder paste thickness tester, an automatic optical detector and an X-ray detector.

4. The control method according to claim 1, characterized in that: The manufacturing execution system includes: a screen printing device, a patch device and a reflow device.

5. The control method according to claim 3, characterized in that: The solder paste thickness tester is used to detect the amount, thickness, offset and solder leakage of solder paste on each pad.

6. The control method according to claim 3, characterized in that: There are two automatic optical detectors, which are used to detect the quality of the patch process and the reflow process respectively.

Images