A manufacturing method, device, system and storage medium for multi-device interaction of an SMT production line

Abstract

Embodiments of the present application disclose a manufacturing method and device, system and medium for SMT production line multi-device interaction. The manufacturing method for SMT production line multi-device interaction comprises: receiving basic measurement data, generating corresponding process scheduling instructions and process data streams according to a preset process and the basic measurement data; a data center stores, updates and distributes the process data streams according to the process scheduling instructions; a process equipment controls the manufacturing process of a circuit board according to the distributed process scheduling instructions and process data streams; a process detection equipment detects the circuit board after the corresponding manufacturing process is performed to generate detection data; and various process deviations are confirmed according to the basic measurement data, detection data and / or the process data streams to achieve full production line collaborative precision compensation. The manufacturing method for SMT production line multi-device interaction achieves the effect of improving manufacturing precision and yield.

Description

Technical Field

[0001] This invention relates to the manufacturing field of multi-device interaction in SMT production lines, and more particularly to a manufacturing method, apparatus, system, and storage medium for multi-device interaction in SMT production lines. Background Technology

[0002] Currently, the manufacturing control of SMT (Surface Mount Technology) production lines is mostly a single-point closed loop or a partial closed loop between two adjacent machines. The machines come from different brands, and their data formats and communication protocols are incompatible, forming serious data silos. Furthermore, due to issues such as pad misalignment, board deformation, and board expansion and contraction during the feeding of FPCB (Flexible Printed Circuit Board) / PCB (Printed Circuit Board) single boards and panelizations, these feeding deviations cannot be effectively identified and corrected. This has become a core obstacle to achieving high-precision manufacturing with existing technologies. Summary of the Invention

[0003] This invention provides a manufacturing method, apparatus, system, and storage medium for multi-device interaction in an SMT production line, which improves manufacturing accuracy and yield.

[0004] According to one aspect of the present invention, a manufacturing method for multi-device interaction in an SMT production line is provided, comprising: The control data center receives basic measurement data of the original circuit board collected online or offline by the precision measuring machine, and generates corresponding process scheduling instructions and process data streams according to the preset process and the basic measurement data. The heterogeneous data received by the data center is converted into a standard format. The heterogeneous data includes at least basic measurement data, detection data, and process data stream. The standardized basic measurement data, detection data, and process data stream are uploaded to the data center, and the data center stores, updates, and distributes the process data stream according to the process scheduling instructions. The control equipment executes the circuit board manufacturing process according to the distributed process scheduling instructions and process data stream; The process control and inspection equipment inspects the circuit board after the corresponding manufacturing process is executed to generate inspection data; Based on the basic measurement data, detection data, and / or the process data stream, various process deviations are identified, and the corresponding process data stream is corrected based on the process deviations; the process equipment is controlled to achieve full-line collaborative accuracy compensation based on the corrected process data stream.

[0005] Optionally, the basic measurement data includes at least one of the following: the coordinates of the whole board reference point, the coordinates of the sub-board reference point, the coordinates of all pads on the sub-board, the offset of each pad, the board deformation data, the positioning hole deviation, and the sub-board partition information. The basic measurement data is bound to the unique number of the circuit board.

[0006] Optionally, the process data stream includes at least one or more of data streams A to H, wherein: Data stream A is the FPCB / PCB single board and panel feeding screening data stream, used to determine the feeding qualification of FPCB / PCB single board and panel due to pad offset, board deformation, or board expansion and contraction, and to realize feeding qualification judgment and intelligent diversion of OK / NG boards; B data stream is the printing press calibration data stream, used to achieve alignment compensation of the printing press due to feed discrepancies; The C data stream is the control data stream for the solder spraying machine, used to achieve precise control of the solder spraying path and coordinates. The D data stream is a composite coordinate data stream that constructs a unified coordinate reference for the offset of the feeding pads of FPCB / PCB single boards and panelizations, board deformation, and board expansion and contraction, in order to realize the construction of a unified coordinate reference between the pick-and-place machine and the AOI in front of the furnace. E data stream is the dispensing machine calibration data stream, which combines deviation data such as FPCB / PCB single board and panel feeding pad offset, board deformation, and board expansion and contraction to realize the calibration of dispensing machine dispensing path or dispensing coordinates. The F data stream is the PCB splitter calibration data stream. It combines the board position and deformation data of the FPCB / PCB single board and panel feeding to realize the calibration of the PCB splitter cutting path or cutting coordinates. The G data stream is the SPI-printer closed-loop data stream, used to correct deviations in the printing press itself, including alignment error, squeegee pressure, angle, and one of the demolding parameters. The H data stream is the closed-loop data stream for AOI-pick-place machine, used to correct the machine's own errors, including placement errors or nozzle errors.

[0007] Optionally, based on the basic measurement data, detection data, and / or the process data stream, multiple process deviations are identified, and the corresponding process data stream is corrected based on the process deviations, including: Based on the coordinate data in the basic measurement data, the pad offset and board deformation are statistically analyzed according to the unique number of the circuit board to generate a first process deviation. The first process deviation is used to correct the A data stream in order to adjust the board splitting process.

[0008] Optionally, based on the detection data and the process data stream, multiple process deviations are identified, and the corresponding process data stream is corrected based on the process deviations, including: A second process deviation is generated based on the full pad coordinates confirmed by the unique circuit board number in the basic measurement data and the preset Gerber file. The second process deviation is used to correct the B data stream in order to adjust the alignment accuracy of the printing press.

[0009] Optionally, based on the basic measurement data, detection data, and / or the process data stream, multiple process deviations are identified, and the corresponding process data stream is corrected based on the process deviations, including: A third process deviation is generated based on the solder paste detection data and the basic measurement data in the detection data. The third process deviation is used to correct the G data stream in order to separate the inherent deviation of the printer and adjust the alignment accuracy of the printer.

[0010] Optionally, based on the basic measurement data, detection data, and / or the process data stream, multiple process deviations are identified, and the corresponding process data stream is corrected based on the process deviations, including: Solder paste printing or solder spraying is performed on the circuit board according to the C data stream; Solder paste inspection is performed on the circuit board based on the D data stream to obtain solder paste inspection data; The mounting offset parameters are confirmed based on the solder paste detection data, component type, and pad position. Based on the component types and pad positions in the basic measurement data, confirm the placement correction parameters, and generate the composite placement coordinates by combining the D data stream; The circuit board is subjected to pre-reflow surface inspection based on the D data stream to obtain placement deviation data. A fourth process deviation is generated based on the mounting deviation data and the basic measurement data. The fourth process deviation is used to correct the H data stream to improve the alignment accuracy of the pick-and-place machine.

[0011] According to another aspect of the present invention, a manufacturing apparatus for multi-device interaction in an SMT production line is provided, comprising: The data processing module is used to receive basic measurement data of the original circuit board collected online or offline by a precision measuring machine, and generate corresponding process scheduling instructions and process data streams according to the preset process and the basic measurement data. The format unification module is used to convert heterogeneous data received by the data center into a standard format. The heterogeneous data includes at least basic measurement data, detection data, and process data streams. The data distribution module uploads the standardized basic measurement data, detection data, and process data stream to the data center. The data center stores, updates, and distributes the process data stream according to the process scheduling instructions. The process execution module is used to execute the circuit board manufacturing process according to the distributed process scheduling instructions and process data stream; The process inspection module is used to inspect the circuit board after the corresponding manufacturing process is executed in order to generate inspection data; The fusion analysis module is used to identify multiple process deviations based on the basic measurement data, detection data, and / or the process data stream, and to correct the corresponding process data stream based on the process deviations; the control process equipment is used to achieve full-line collaborative accuracy compensation based on the corrected process data stream.

[0012] According to another aspect of the present invention, a manufacturing system for multi-device interaction in an SMT production line is provided, comprising: one or more processors; a memory for storing one or more programs; wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the above-described manufacturing method for multi-device interaction in an SMT production line.

[0013] According to another aspect of the present invention, a storage medium is provided on which a computer program is stored, which, when executed by a processor, implements the above-described manufacturing method for multi-device interaction in an SMT production line.

[0014] Compared to existing technologies, the above method accurately solves the manufacturing precision deviations caused by pad offset, board deformation, and board expansion and contraction in FPCB / PCB single boards and panels, thereby improving the ability to compensate for incoming material deviations. Specifically, the method in this case establishes a refined measurement, deviation analysis, and precise compensation system specifically for the inherent deviations of incoming single boards and panels. It can effectively capture and correct deviations such as pad offset, board deformation, and board expansion and contraction based on the basic measurement data of the original circuit board, significantly improving the production precision and product yield of the corresponding processes. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of a manufacturing method for multi-device interaction in an SMT production line provided in Embodiment 1 of the present invention.

[0017] Figure 2 This is a flowchart of a multi-device interaction manufacturing apparatus for an SMT production line provided in Embodiment 2 of the present invention.

[0018] Figure 3 This is a schematic diagram of a multi-device interactive manufacturing system for an SMT production line provided in Embodiment 3 of the present invention. Detailed Implementation

[0019] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0020] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data used can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0021] Example 1 Figure 1 This is a flowchart of a manufacturing method for multi-device interaction in an SMT production line according to Embodiment 1 of the present invention. This embodiment can be applied to a manufacturing apparatus for multi-device interaction in an SMT production line. This apparatus can be implemented in software and / or hardware and is generally integrated into a manufacturing system for multi-device interaction in an SMT production line. Correspondingly, such as... Figure 1 As shown, the method includes the following steps.

[0022] S110. The control data center receives the basic measurement data of the original circuit board collected online or offline by the precision measurement machine, and generates corresponding process scheduling instructions and process data streams according to the preset process and the basic measurement data.

[0023] In one embodiment, a high-precision measuring machine with an absolute error of less than or equal to ±10μm and a repeatability of less than or equal to 1μm is used to perform a full-size high-precision scan on the incoming circuit board to obtain basic measurement data. In one embodiment, the basic measurement data includes at least one or more of the following: the coordinates of the entire board reference point of the incoming circuit board, the coordinates of the sub-board reference point, the coordinates of all pads on the sub-board, the positioning hole deviation, and the sub-board partition information.

[0024] Preferably, the basic measurement data of each incoming circuit board is bound to its unique code and sub-board partition information, serving as the sole data source for the entire production line. In this embodiment, the measuring machine can be positioned before the soldering machine station. After performing a high-precision scan of the incoming circuit board and acquiring the basic measurement data, the data is standardized, stored, and forwarded to subsequent process equipment, such as the soldering machine, solder paste inspection machine, pre-reflow AOI and post-reflow AOI, dispensing machine, and / or depaneling machine. In an alternative embodiment, the measuring machine can also be set up independently rather than on the production line. This allows for a high-precision scan of each PCB or FPCB before it enters the warehouse to acquire basic measurement data. The basic measurement data is then standardized, transmitted via network equipment, and stored in a data center, cloud server, or host computer. During actual production, subsequent process equipment only needs to read the corresponding basic measurement data from the data center, cloud server, or host computer to perform its functions.

[0025] In one embodiment, the process data stream includes at least one or more of data streams A to H, wherein: Data stream A is the FPCB / PCB single board and panel feeding screening data stream, used to determine the feeding qualification of FPCB / PCB single board and panel due to pad offset, board deformation, or board expansion and contraction, and to realize feeding qualification judgment and intelligent diversion of OK / NG boards; B data stream is the printing press calibration data stream, used to achieve alignment compensation of the printing press due to feed discrepancies; The C data stream is the control data stream for the solder spraying machine, used to achieve precise control of the solder spraying path and coordinates. The D data stream is a composite coordinate data stream that constructs a unified coordinate reference for the offset of the feeding pads of FPCB / PCB single boards and panelizations, board deformation, and board expansion and contraction, in order to realize the construction of a unified coordinate reference between the pick-and-place machine and the AOI in front of the furnace. E data stream is the dispensing machine calibration data stream, which combines deviation data such as FPCB / PCB single board and panel feeding pad offset, board deformation, and board expansion and contraction to realize the calibration of dispensing machine dispensing path or dispensing coordinates. The F data stream is the PCB splitter calibration data stream. It combines the board position and deformation data of the FPCB / PCB single board and panel feeding to realize the calibration of the PCB splitter cutting path or cutting coordinates. The G data stream is the SPI-printer closed-loop data stream, used to correct deviations in the printing press itself, including alignment error, squeegee pressure, angle, and one of the demolding parameters. The H data stream is the closed-loop data stream for AOI-pick-place machine, used to correct the machine's own errors, including placement errors or nozzle errors.

[0026] S120. Convert the heterogeneous data received by the data center into a standard format. The heterogeneous data includes at least basic measurement data, detection data, and process data stream.

[0027] In this embodiment, the data standardization processing module (format unification module) unifies all heterogeneous data collected by the data center and performs format conversion to generate a standard data model with a unified format. This enables a unified coordinate system for the entire production line and eliminates data barriers between different devices.

[0028] S130. The standardized basic measurement data, detection data, and process data stream are uploaded to the data center. The data center stores, updates, and distributes the process data stream according to the process scheduling instructions.

[0029] In this embodiment, all data streams are generated from the same source of basic measurement data. The data center can accurately send deviation data such as pad offset, board deformation, and board expansion and contraction of FPCB / PCB single board and panel to each data stream. Each data stream can be implemented independently to achieve accuracy improvement and closed-loop control of the corresponding process. Alternatively, multiple data streams can be combined to achieve collaborative optimization and advanced closed-loop effect of the corresponding process.

[0030] S140: The control process equipment executes the circuit board manufacturing process according to the distributed process scheduling instructions and process data stream.

[0031] In this embodiment, the process equipment mainly includes a metrology machine, a printer, a pick-and-place machine, a dispensing machine, and / or a depaneling machine. All process equipment interacts bidirectionally with the data hub via a network, ensuring the stable transmission of basic measurement data, equipment operation data, and process data. This ensures that each process device can obtain basic measurement data and corresponding process data streams from the unified data hub as needed to execute the corresponding process, while simultaneously uploading its own status data to the data hub in real time.

[0032] S150. The process control inspection equipment inspects the circuit board after the corresponding manufacturing process is executed to generate inspection data. In this embodiment, the process inspection equipment includes a solder paste inspection machine (SPI), an automated optical inspection (AOI) for the furnace front, and / or an AOI for the furnace back. All process inspection equipment and the data center also interact bidirectionally through the network to ensure the stable transmission of basic measurement data, equipment operation data, process data, and inspection data. This ensures that each process inspection device can obtain basic measurement data and corresponding process data streams from the unified data center as needed, so as to perform standardized and highly accurate inspections.

[0033] S160. Based on the basic measurement data, detection data and / or the process data stream, identify multiple process deviations, and correct the corresponding process data stream based on the process deviations; control the process equipment to achieve full-line collaborative accuracy compensation based on the corrected process data stream.

[0034] In one embodiment, identifying multiple process deviations based on the basic measurement data, detection data, and / or the process data stream, and correcting the corresponding process data stream based on the process deviations includes: Based on the coordinate data in the basic measurement data, the pad offset and board deformation are statistically analyzed according to the unique number of the circuit board to generate a first process deviation. The first process deviation is used to correct the A data stream in order to adjust the board splitting process.

[0035] Specifically, the actual coordinate data of the pads in the incoming circuit board is confirmed based on the marker points and coordinate data in the basic measurement data; coordinate system alignment is performed based on the marker points in the basic measurement data of the circuit board and the Mark coordinate data (also known as reference points or fiducial marks) in the preset Gerber data of the circuit board (which are key reference data in PCB manufacturing and SMT assembly processes, used for precise alignment and inter-layer alignment); target translation and target rotation angles are determined based on the actual coordinate data of the pads and the preset Gerber data of the incoming circuit board, so that the global alignment error of all pads between the preset Gerber data and the actual coordinate data of the pads is minimized; solder paste printing coordinate simulation data is generated based on the preset Gerber data, the target translation, and the target rotation angle; the solder paste printing coordinate simulation data is compared with the actual coordinate data of the pads one by one to obtain pad deviation data (first process deviation); if the root mean square error is less than the preset whole board error threshold, the incoming circuit board is determined to be qualified. Alternatively, the coordinate distance offset and / or the rotation angle offset (first process deviation) can be compared with a preset single-point error threshold. If the number of pads exceeding the preset single-point error threshold is less than or equal to a preset value, the incoming circuit board is determined to be qualified. Qualified incoming materials flow to subsequent workstations, while unqualified incoming materials flow into a waste bin.

[0036] Specifically, the actual coordinate data of the pads and the centroid of the pads in the preset Gerber data can be calculated separately; the centered coordinates of each pad in the actual coordinate data of the pads and the preset Gerber data can be calculated based on the centroid of the pads, and the covariance term between the two types of centered coordinates can be calculated; the target rotation angle can be calculated based on the covariance term, and the target translation amount can be calculated based on the target rotation angle and the centroid of the pads.

[0037] In one embodiment, multiple process deviations are identified based on the detection data and the process data stream, and the corresponding process data stream is corrected based on the process deviations, including: A second process deviation is generated based on the full pad coordinates confirmed by the unique circuit board number in the basic measurement data and the preset Gerber file. The second process deviation is used to correct the B data stream in order to adjust the alignment accuracy of the printing press.

[0038] In one embodiment, the coordinates of the marked points and the actual coordinates of the pads in the incoming circuit board are obtained based on the basic measurement data, as well as the coordinates of the stencil reference points and the reference coordinates of the pads in the printing press. The reference point is aligned based on the coordinates of the marked point and the coordinates of the steel mesh reference point to obtain the reference point offset compensation data (second process deviation). The pads are aligned based on the actual coordinate data and the reference coordinate data of the pads to obtain pad offset compensation data (second process deviation). Based on the reference point offset compensation data and the pad offset compensation data, the incoming material deviation compensation data is determined so that the printer can perform compensation calibration (correction B data stream) based on the incoming material deviation compensation data.

[0039] In one embodiment, identifying multiple process deviations based on the basic measurement data, detection data, and / or the process data stream, and correcting the corresponding process data stream based on the process deviations includes: A third process deviation is generated based on the solder paste detection data and the basic measurement data in the detection data. The third process deviation is used to correct the G data stream in order to separate the inherent deviation of the printer and adjust the alignment accuracy of the printer.

[0040] Specifically, after solder paste is printed on the circuit board according to the B data stream, the circuit board is transported to the station of the solder paste inspection machine; the circuit board is inspected for solder paste according to the D data stream to obtain solder paste inspection data; the solder paste inspection machine performs high-precision positioning of the sub-board reference points of each sub-board to generate sub-board positioning results; based on the sub-board positioning results, the solder paste at each pad of the sub-board is collected point by point to obtain the solder paste inspection data; the actual printing deviation (third process deviation) is confirmed according to the solder paste inspection data of the circuit board and the basic measurement data; the G data stream is corrected according to the actual printing deviation to separate the inherent deviation of the printing machine (adjust the printing force, angle, and solder paste thickness) and adjust the alignment accuracy of the printing machine (fine-tune the position and angle of the printing screen).

[0041] In one embodiment, multiple process deviations are identified based on the basic measurement data, detection data, and / or the process data stream. Correcting the corresponding process data stream based on the process deviations includes: performing solder paste printing or solder spraying on the circuit board according to the C data stream; performing solder paste detection on the circuit board according to the D data stream to obtain solder paste detection data; identifying placement offset parameters based on the solder paste detection data, component type, and pad position; identifying placement correction parameters based on component type and pad position in the basic measurement data, and generating placement composite coordinates in combination with the D data stream; performing pre-reflow placement detection on the circuit board according to the D data stream to obtain placement deviation data; and generating a fourth process deviation based on the placement deviation data and the basic measurement data. The fourth process deviation is used to correct the H data stream to improve the alignment accuracy of the pick-and-place machine.

[0042] Specifically, first confirm the component information corresponding to each pad; based on the component information (mounting size and soldering process) of the component to be mounted, confirm the solder paste offset weighting coefficient k corresponding to the component to be mounted; unify the coordinate system of the high-precision data and the solder paste detection data; based on the pad coordinates in the high-precision data, confirm the component mounting coordinates A(x,y); based on the offset data of the solder paste detection data relative to the pad coordinates, confirm the component mounting position offset BA(x,y); based on the solder paste offset weighting coefficient k and the component mounting coordinates... A(x,y) and the component placement position offset BA(x,y) generate the component placement composite coordinates. The composite coordinates are calculated as follows: C(x,y)=A(x,y)+k×BA(x,y). The pick-and-place machine performs the component placement process based on the composite coordinates. After placement, the AOI equipment detects the placement result based on the composite coordinates to generate a placement detection deviation (fourth process deviation). The fourth process deviation is used to correct the H data stream to further improve the alignment accuracy of the pick-and-place machine.

[0043] Among them, the component types include three categories. The first category of components (k = 0) are large-sized components: C(x,y) = A(x,y), and the synthesized coordinates are exactly equal to the mounting coordinates after the conversion of the pad coordinates, ensuring that the pins of the large-sized components are precisely aligned with the pads and meeting the welding reliability requirements of their high alignment accuracy. The second category of components (0 < k < 1, with the default k = 0.5) are medium-sized components: C(x,y) = A(x,y) + 0.5×BA(x,y), and the synthesized coordinates are the weighted average of the component mounting coordinates calculated from the basic measurement data and the mounting offset after SPI conversion, taking into account both the welding reliability of the medium-sized components and the influence of the surface tension of the reflow soldering. The third category of components (k = 1) are small-sized components: C(x,y) = A(x,y) + BA(x,y), and the synthesized coordinates are equal to the component mounting coordinates calculated from the basic measurement data plus the mounting position offset after SPI conversion, that is, the mounting coordinates matching the actual distribution of the solder paste, ensuring that the micro-components are precisely mounted at the center of the solder paste, avoiding the displacement of the components during reflow soldering, and meeting the high dependence requirements of the micro-components on the distribution position of the solder paste. In this embodiment, C(x,y) is the x / y-axis coordinate value of the final synthesized mounting coordinates of the components.

[0044] In this embodiment, the D data stream integrates the coordinate of the entire board pads, the solder paste coordinate of the entire board, and the data of the final synthesized mounting coordinates of the component mounting. These data need to be saved throughout the entire process of circuit board production. In one embodiment, the D data is stored in a structured database and supports multi-dimensional retrieval, realizing the systematic association and traceability of the entire life cycle of the data. At the same time, it can be synchronized to the existing MES system and QMS system on the circuit board production line, providing data support for the digital control of the entire SMT production process.

[0045] In one embodiment, the pre-furnace AOI extracts the overall board reference coordinates, sub-board reference coordinates, and sub-board pad coordinates according to the D data stream corresponding to the unique number of the circuit board. The pre-furnace AOI performs a full-size scan detection of each component on the entire board, and identifies the physical contour of each component through an image recognition algorithm. Based on the sub-board reference coordinates, the accurate actual X / Y-axis coordinates and the actual rotation angle value of each component after mounting are determined through a positioning algorithm. The pre-furnace AOI synchronously collects at least one of the component misplacement, missing component, or reverse component as the mounting quality data. The component offset and rotation data between the accurate actual X / Y-axis coordinates and the actual rotation angle value of the component after mounting and the synthesized mounting coordinates and the standard rotation angle in the D data stream are compared. The component offset and rotation data and the mounting quality data are integrated to generate the H data stream.

[0046] In one embodiment, after receiving offset rotation data and placement quality data from the H data stream, the pick-and-place machine autonomously generates adjustment parameters and completes correction actions. Based on the offset rotation data, it adjusts parameters such as placement coordinates and rotation angles to complete the position offset correction of the corresponding components on the next FPCB / PCB of the same batch. At the same time, based on the placement quality data, it autonomously completes program modification, nozzle parameters and other related parameter adjustments.

[0047] In one embodiment, the pick-and-place machine performs a closed-loop calibration based on the H data stream, including: performing full-size inspection on the next calibrated FPCB / PCB after reflow AOI, collecting the actual position coordinates, rotation angle, and mounting quality data of the components, and feeding them back to the data center of the production line host computer or server. The data center compares the deviation of the actual position and rotation angle of the components before and after calibration with the composite mounting coordinates and standard rotation angle, as well as the mounting quality. If the deviation is ≤ a preset qualified threshold and the mounting quality meets the standard, the closed-loop calibration is deemed effective, and the offset rotation data of this calibration is included in the basic data of the same batch of FPCB / PCB for subsequent mounting. If the deviation exceeds the preset threshold or the mounting quality does not meet the standard, the error source is separated by combining the D data stream and AOI detection data again, the offset rotation data is recalculated, and the mounting quality data is integrated to generate an H data stream and sent to the pick-and-place machine to form a dynamic closed loop until the mounting deviation meets the standard requirements of high-precision mounting and the mounting quality meets the standard.

[0048] Compared to existing technologies, the multi-device interaction manufacturing method for SMT production lines in this embodiment has the following advantages: 1. It can implement drive control for any single or multiple functional data streams. Specifically, the above method can solve manufacturing precision defects caused by pad offset, board deformation, and board expansion / contraction in FPCB / PCB single boards and panelizations, and improve the compensation capability for incoming material deviations: it establishes a refined measurement, deviation analysis, and accurate compensation system specifically for inherent deviations in incoming materials, which can effectively capture and correct deviations such as pad offset, board deformation, and board expansion / contraction, thereby improving the production accuracy and product yield of the corresponding processes.

[0049] The above method completely breaks down data silos and achieves efficient data exchange across the entire production line: The data hub of this solution achieves bidirectional connection with other data centers and process equipment through network communication modules, and establishes standardized communication links through network communication modules. Combined with a data flow system with the same source functions, it achieves data compatibility and sharing for equipment of all brands and processes, fundamentally solving the problem of data silos.

[0050] The above method achieves a qualitative leap in closed-loop accuracy and avoids blind compensation: it accurately separates various error sources through multivariate coupling analysis, and cross-device linkage compensation based on the same source data stream replaces single-point local closed loop, which greatly improves the accuracy of closed-loop compensation and effectively reduces the batch defect rate.

[0051] The above-mentioned method has a well-developed standardized data flow system, which constructs a functional data flow system with the original basic measurement dataset as the sole source, extends the core data of the measurement machine to the corresponding production process, greatly improves data utilization, and fully releases the value of core data.

[0052] The above method enables precise traceability throughout the entire process and proactive control of quality risks: it achieves the association and storage of full lifecycle data in a unified data center by FPCB / PCB number and board number, which greatly shortens the time for quality problem investigation and can accurately trace the root cause of the problem; the proactive early warning function can effectively avoid quality risks, especially batch defects caused by incoming material pad misalignment, board deformation, and board expansion and contraction.

[0053] 2. The above method can also achieve advanced effects such as full process coverage (achievable through AH full-process functional data flow implementation). Specifically, based on the global analysis and scheduling of the full production line's full-process functional data flow, the above method can accurately identify production line bottlenecks and optimize parameters for all processes, effectively improving production line efficiency, reducing downtime for calibration, and lowering maintenance costs.

[0054] The above method uses a dedicated data distribution module to ensure the stability of the entire data stream transmission. The data transmission and closed-loop response speed are adapted to the cycle time requirements of high-speed SMT production lines, avoiding production errors caused by data transmission problems.

[0055] The above method supports access to all mainstream SMT equipment brands. It can be linked with a unified data hub through the equipment network communication module without the need for large-scale modification of existing production lines. It can be adapted to various SMT production lines and has made full-process exclusive optimizations for FPCB / PCB single board and panel material pad offset, board deformation, and board expansion and contraction. Its versatility covers the entire production scenario.

[0056] Example 2 Figure 2 This is a schematic diagram of a multi-device interactive manufacturing apparatus for an SMT production line according to Embodiment 2 of the present invention. The apparatus 200 can be implemented by software and / or hardware, and is generally integrated into a multi-device interactive manufacturing system for an SMT production line, such as... Figure 2 As shown, the device 200 includes: a data processing module 210, a format unification module 220, a data distribution module 230, a process execution module 240, a process detection module 250, and a fusion analysis module 260.

[0057] The data processing module 210 is used to receive basic measurement data of the original circuit board collected online or offline by a precision measuring machine, and generate corresponding process scheduling instructions and process data streams according to the preset process and the basic measurement data.

[0058] In one embodiment, a high-precision measuring machine with an absolute error of less than or equal to ±10μm and a repeatability of less than or equal to 1μm is used to perform a full-size high-precision scan on the incoming circuit board to obtain basic measurement data. In one embodiment, the basic measurement data includes at least one or more of the following: the coordinates of the entire board reference point of the incoming circuit board, the coordinates of the sub-board reference point, the coordinates of all pads on the sub-board, the positioning hole deviation, and the sub-board partition information.

[0059] Preferably, the basic measurement data of each incoming circuit board is bound to its unique code and sub-board partition information, serving as the sole data source for the entire production line. In this embodiment, the measuring machine can be positioned before the soldering machine station. After performing a high-precision scan of the incoming circuit board and acquiring the basic measurement data, the data is standardized, stored, and forwarded to subsequent process equipment, such as the soldering machine, solder paste inspection machine, pre-reflow AOI and post-reflow AOI, dispensing machine, and / or depaneling machine. In an alternative embodiment, the measuring machine can also be set up independently rather than on the production line. This allows for a high-precision scan of each PCB or FPCB before it enters the warehouse to acquire basic measurement data. The basic measurement data is then standardized, transmitted via network equipment, and stored in a data center, cloud server, or host computer. During actual production, subsequent process equipment only needs to read the corresponding basic measurement data from the data center, cloud server, or host computer to perform its functions.

[0060] In one embodiment, the process data stream includes at least one or more of data streams A to H, wherein: Data stream A is the FPCB / PCB single board and panel feeding screening data stream, used to determine the feeding qualification of FPCB / PCB single board and panel due to pad offset, board deformation, or board expansion and contraction, and to realize feeding qualification judgment and intelligent diversion of OK / NG boards; B data stream is the printing press calibration data stream, used to achieve alignment compensation of the printing press due to feed discrepancies; The C data stream is the control data stream for the solder spraying machine, used to achieve precise control of the solder spraying path and coordinates. The D data stream is a composite coordinate data stream that constructs a unified coordinate reference for the offset of the feeding pads of FPCB / PCB single boards and panelizations, board deformation, and board expansion and contraction, in order to realize the construction of a unified coordinate reference between the pick-and-place machine and the AOI in front of the furnace. E data stream is the dispensing machine calibration data stream, which combines deviation data such as FPCB / PCB single board and panel feeding pad offset, board deformation, and board expansion and contraction to realize the calibration of dispensing machine dispensing path or dispensing coordinates. The F data stream is the PCB splitter calibration data stream. It combines the board position and deformation data of the FPCB / PCB single board and panel feeding to realize the calibration of the PCB splitter cutting path or cutting coordinates. The G data stream is the SPI-printer closed-loop data stream, used to correct deviations in the printing press itself, including alignment error, squeegee pressure, angle, and one of the demolding parameters. The H data stream is the closed-loop data stream for AOI-pick-place machine, used to correct the machine's own errors, including placement errors or nozzle errors.

[0061] The format unification module 220 is used to convert heterogeneous data received by the data center into a standard format. The heterogeneous data includes at least basic measurement data, detection data, and process data streams.

[0062] In this embodiment, the data standardization processing module (format unification module) unifies all heterogeneous data collected by the data center and performs format conversion to generate a standard data model with a unified format. This enables a unified coordinate system for the entire production line and eliminates data barriers between different devices.

[0063] The data distribution module 230 uploads the standardized basic measurement data, detection data, and process data stream to the data center. The data center stores, updates, and distributes the process data stream according to the process scheduling instructions.

[0064] In this embodiment, all data streams are generated from the same source of basic measurement data. The data center can accurately send deviation data such as pad offset, board deformation, and board expansion and contraction of FPCB / PCB single board and panel to each data stream. Each data stream can be implemented independently to achieve accuracy improvement and closed-loop control of the corresponding process. Alternatively, multiple data streams can be combined to achieve collaborative optimization and advanced closed-loop effect of the corresponding process.

[0065] The process execution module 240 is used to execute the manufacturing process of the circuit board according to the distributed process scheduling instructions and process data stream.

[0066] In this embodiment, the process equipment mainly includes a metrology machine, a printer, a pick-and-place machine, a dispensing machine, and / or a depaneling machine. All process equipment interacts bidirectionally with the data hub via a network, ensuring the stable transmission of basic measurement data, equipment operation data, and process data. This ensures that each process device can obtain basic measurement data and corresponding process data streams from the unified data hub as needed to execute the corresponding process, while simultaneously uploading its own status data to the data hub in real time.

[0067] The process inspection module 250 is used to inspect the circuit board after the corresponding manufacturing process is executed to generate inspection data.

[0068] In this embodiment, the process inspection equipment includes SPI, furnace front AOI and / or furnace back AOI. All process inspection equipment and the data hub also interact bidirectionally through the network to ensure the stable transmission of basic measurement data, equipment operation data, process data and inspection data. This ensures that each process inspection equipment can obtain basic measurement data and corresponding process data streams from the unified data hub as needed to perform standardized and highly accurate inspections.

[0069] The fusion analysis module 260 is used to identify multiple process deviations based on the basic measurement data, detection data and / or the process data stream, correct the corresponding process data stream based on the process deviations, and control the process equipment to achieve full-line collaborative accuracy compensation based on the corrected process data stream.

[0070] In one embodiment, identifying multiple process deviations based on the basic measurement data, detection data, and / or the process data stream, and correcting the corresponding process data stream based on the process deviations includes: Based on the coordinate data in the basic measurement data, the pad offset and board deformation are statistically analyzed according to the unique number of the circuit board to generate a first process deviation. The first process deviation is used to correct the A data stream in order to adjust the board splitting process.

[0071] Specifically, the actual coordinate data of the pads in the incoming circuit board is confirmed based on the marker points and coordinate data in the basic measurement data; coordinate system alignment is performed based on the marker points in the basic measurement data of the circuit board and the Mark coordinate data in the preset Gerber data of the circuit board; target translation and target rotation angles are determined based on the actual coordinate data of the pads and the preset Gerber data of the incoming circuit board, so that the global alignment error of all pads between the preset Gerber data and the actual coordinate data of the pads is minimized after the preset Gerber data is adjusted based on the target translation and target rotation angle; solder paste printing coordinate simulation data is generated based on the preset Gerber data, the target translation, and the target rotation angle; the solder paste printing coordinate simulation data is compared with the actual coordinate data of the pads one by one to obtain pad deviation data (first process deviation); if the root mean square error is less than the preset whole board error threshold, the incoming circuit board is determined to be qualified. Alternatively, the coordinate distance offset and / or the rotation angle offset (first process deviation) can be compared with a preset single-point error threshold. If the number of pads exceeding the preset single-point error threshold is less than or equal to a preset value, the incoming circuit board is determined to be qualified. Qualified incoming materials flow to subsequent workstations, while unqualified incoming materials flow into a waste bin.

[0072] Specifically, the actual coordinate data of the pads and the centroid of the pads in the preset Gerber data can be calculated separately; the centered coordinates of each pad in the actual coordinate data of the pads and the preset Gerber data can be calculated based on the centroid of the pads, and the covariance term between the two types of centered coordinates can be calculated; the target rotation angle can be calculated based on the covariance term, and the target translation amount can be calculated based on the target rotation angle and the centroid of the pads.

[0073] In one embodiment, multiple process deviations are identified based on the detection data and the process data stream, and the corresponding process data stream is corrected based on the process deviations, including: A second process deviation is generated based on the full pad coordinates confirmed by the unique circuit board number in the basic measurement data and the preset Gerber file. The second process deviation is used to correct the B data stream in order to adjust the alignment accuracy of the printing press.

[0074] In one embodiment, the coordinates of the marked points and the actual coordinates of the pads in the incoming circuit board are obtained based on the basic measurement data, as well as the coordinates of the stencil reference points and the reference coordinates of the pads in the printing press. The reference point is aligned based on the coordinates of the marked point and the coordinates of the steel mesh reference point to obtain the reference point offset compensation data (second process deviation). The pads are aligned based on the actual coordinate data and the reference coordinate data of the pads to obtain pad offset compensation data (second process deviation). Based on the reference point offset compensation data and the pad offset compensation data, the incoming material deviation compensation data is determined so that the printer can perform compensation calibration (correction B data stream) based on the incoming material deviation compensation data.

[0075] In one embodiment, identifying multiple process deviations based on the basic measurement data, detection data, and / or the process data stream, and correcting the corresponding process data stream based on the process deviations includes: A third process deviation is generated based on the solder paste detection data and the basic measurement data in the detection data. The third process deviation is used to correct the G data stream in order to separate the inherent deviation of the printer and adjust the alignment accuracy of the printer.

[0076] Specifically, after solder paste is printed on the circuit board according to the B data stream, the circuit board is transported to the station of the solder paste inspection machine; the circuit board is inspected for solder paste according to the D data stream to obtain solder paste inspection data; the solder paste inspection machine performs high-precision positioning of the sub-board reference points of each sub-board to generate sub-board positioning results; based on the sub-board positioning results, the solder paste at each pad of the sub-board is collected point by point to obtain the solder paste inspection data; the actual printing deviation (third process deviation) is confirmed according to the solder paste inspection data of the circuit board and the basic measurement data; the G data stream is corrected according to the actual printing deviation to separate the inherent deviation of the printing machine (adjust the printing force, angle, and solder paste thickness) and adjust the alignment accuracy of the printing machine (fine-tune the position and angle of the printing screen).

[0077] In one embodiment, multiple process deviations are identified based on the basic measurement data, detection data, and / or the process data stream. Correcting the corresponding process data stream based on the process deviations includes: performing solder paste printing or solder spraying on the circuit board according to the C data stream; performing solder paste detection on the circuit board according to the D data stream to obtain solder paste detection data; identifying placement offset parameters based on the solder paste detection data, component type, and pad position; identifying placement correction parameters based on component type and pad position in the basic measurement data, and generating placement composite coordinates in combination with the D data stream; performing pre-reflow placement detection on the circuit board according to the D data stream to obtain placement deviation data; and generating a fourth process deviation based on the placement deviation data and the basic measurement data. The fourth process deviation is used to correct the H data stream to improve the alignment accuracy of the pick-and-place machine.

[0078] Specifically, the component information corresponding to each pad can be confirmed; the solder paste offset weight coefficient k corresponding to the component to be mounted can be confirmed based on the component information (mounting size and soldering process); The coordinate system of high-precision data and solder paste inspection data is unified; the component placement coordinates A(x,y) are determined based on the pad coordinates in the high-precision data, and the component placement position offset BA(x,y) is determined based on the offset data of the solder paste inspection data relative to the pad coordinates. The component placement composite coordinates are generated based on the solder paste offset weighting coefficient k, the component placement coordinates A(x,y), and the component placement position offset BA(x,y). The calculation method of the composite coordinates is: C(x,y)=A(x,y)+k×BA(x,y). The pick-and-place machine performs the component placement process according to the composite coordinates. After placement, the AOI equipment detects the placement result based on the composite coordinates to generate a placement detection deviation (fourth process deviation). The fourth process deviation is used to correct the H data stream to further improve the alignment accuracy of the pick-and-place machine.

[0079] Among them, the component types include three categories. The first category of components (k = 0) are large-sized components: C(x,y) = A(x,y), and the synthesized coordinates are exactly equal to the mounting coordinates converted from the pad coordinates, ensuring that the pins of the large-sized components are precisely aligned with the pads and meeting the welding reliability requirements of their high alignment accuracy; The second category of components (0 < k < 1, default k = 0.5) are medium-sized components: C(x,y) = A(x,y) + 0.5×BA(x,y), and the synthesized coordinates are the weighted average of the mounting coordinates of the measuring machine and the mounting offset after SPI conversion, taking into account the welding reliability of medium-sized components and the influence of the surface tension of reflow soldering; The third category of components (k = 1) are small-sized components: C(x,y) = A(x,y) + BA(x,y), and the synthesized coordinates are equal to the mounting coordinates of the measuring machine plus the mounting position offset after SPI conversion, that is, the mounting coordinates matching the actual distribution of solder paste, ensuring that the micro-components are precisely mounted at the center of the solder paste, avoiding the displacement of components during reflow soldering, and meeting the high dependence requirements of micro-components on the distribution position of solder paste. In this embodiment, C(x,y) is the x / y-axis coordinate value of the final mounting synthesized coordinates of the component.

[0080] The above manufacturing device for multi-device interaction in the SMT production line can execute the manufacturing method for multi-device interaction in the SMT production line provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method. For technical details not described in detail in this embodiment, reference can be made to the manufacturing method for multi-device interaction in the SMT production line provided by any embodiment of the present invention. Since the above-introduced manufacturing device for multi-device interaction in the SMT production line is a device that can execute the manufacturing method for multi-device interaction in the SMT production line in the embodiments of the present invention, based on the manufacturing method for multi-device interaction in the SMT production line introduced in the embodiments of the present invention, those skilled in the art can understand the specific implementation manners and various variations of the manufacturing device for multi-device interaction in the SMT production line in this embodiment. Therefore, the implementation of how the manufacturing device for multi-device interaction in the SMT production line realizes the manufacturing method for multi-device interaction in the SMT production line in the embodiments of the present invention will not be described in detail here. As long as the device adopted by those skilled in the art to implement the manufacturing method for multi-device interaction in the SMT production line in the embodiments of the present invention belongs to the scope to be protected by this application.

[0081] Embodiment III Figure 3 shows a schematic structural diagram of a manufacturing system for multi-device interaction in the SMT production line provided by Embodiment III of the present invention. As Figure 3As shown, the SMT production line multi-device interactive manufacturing system 300 includes the aforementioned SMT production line multi-device interactive manufacturing apparatus 200. The SMT production line multi-device interactive manufacturing apparatus 200 includes at least one processor 11 and a memory (only the detailed structure of the local conference host is shown in the figure) communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. The RAM 13 can also store various programs and data required for the operation of the SMT production line multi-device interactive manufacturing system 300. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0082] The multi-device interactive manufacturing system 300 for SMT production lines has multiple components connected to I / O interface 15, including: input units 16, such as keyboards and mice; output units 17, such as various types of displays and speakers; storage units 18, such as disks and optical discs; and communication units 19, such as network cards, modems, and wireless transceivers. Communication unit 19 allows the multi-device interactive manufacturing system 300 for SMT production lines to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0083] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the processor in a manufacturing apparatus 200 for multi-device interaction in an SMT production line implementing a manufacturing method for multi-device interaction in an SMT production line.

[0084] In some embodiments, the SMT production line multi-device interaction manufacturing method can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed via ROM 12 and / or communication unit 19 onto one of the process equipment at any station of the SMT production line multi-device interaction manufacturing apparatus 200 of the SMT production line multi-device interaction manufacturing system 300, such as a high-precision measuring machine, printer, solder paste inspector, pre-reflow AOI, post-reflow AOI, dispensing machine, and depaneling machine, or it can be loaded and / or installed separately onto a host computer or server of the SMT production line multi-device interaction manufacturing system 300 as a data processing module. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the SMT production line multi-device interaction manufacturing method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the SMT production line multi-device interaction manufacturing method by any other suitable means (e.g., by means of firmware).

[0085] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0086] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0087] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0088] To provide interaction with a user, the systems and techniques described herein can be implemented on a mobile terminal having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the mobile terminal. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0089] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0090] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0091] Example 4 Embodiment 4 of the present invention also provides a computer storage medium for storing a computer program, which, when executed by a computer processor, is used to perform the manufacturing method for multi-device interaction in an SMT production line as described in any of the above embodiments of the present invention.

[0092] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM, or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0093] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0094] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, radio frequency (RF), or any suitable combination thereof.

[0095] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A manufacturing method for multi-device interaction in an SMT production line, characterized in that, include: The control data center receives basic measurement data of the original circuit board collected online or offline by the precision measuring machine, and generates corresponding process scheduling instructions and process data streams according to the preset process and the basic measurement data. The heterogeneous data received by the data center is converted into a standard format. The heterogeneous data includes at least basic measurement data, detection data, and process data stream. The standardized basic measurement data, detection data, and process data stream are uploaded to the data center, and the data center stores, updates, and distributes the process data stream according to the process scheduling instructions. The control equipment executes the circuit board manufacturing process according to the distributed process scheduling instructions and process data stream; The process control and inspection equipment inspects the circuit board after the corresponding manufacturing process is executed to generate inspection data; Based on the basic measurement data, detection data, and / or the process data stream, various process deviations are identified, and the corresponding process data stream is corrected based on the process deviations; the process equipment is controlled to achieve full-line collaborative accuracy compensation based on the corrected process data stream.

2. The manufacturing method for multi-device interaction in an SMT production line according to claim 1, characterized in that, The basic measurement data includes at least one of the following: the coordinates of the whole board reference point, the coordinates of the sub-board reference point, the coordinates of all pads on the sub-board, the offset of each pad, the board deformation data, the positioning hole deviation, and the sub-board partition information. The basic measurement data is bound to the unique number of the circuit board.

3. The manufacturing method for multi-device interaction in an SMT production line according to claim 2, characterized in that, The process data stream includes at least one or more of data streams A to H, wherein: Data stream A is the FPCB / PCB single board and panel feeding screening data stream, used to determine the feeding qualification of FPCB / PCB single board and panel due to pad offset, board deformation, or board expansion and contraction, and to realize feeding qualification judgment and intelligent diversion of OK / NG boards; B data stream is the printing press calibration data stream, used to achieve alignment compensation of the printing press due to feed discrepancies; The C data stream is the control data stream for the solder spraying machine, used to achieve precise control of the solder spraying path and coordinates. The D data stream is a composite coordinate data stream that constructs a unified coordinate reference for the offset of the feeding pads of FPCB / PCB single boards and panelizations, board deformation, and board expansion and contraction, in order to realize the construction of a unified coordinate reference between the pick-and-place machine and the AOI in front of the furnace. E data stream is the dispensing machine calibration data stream, which combines deviation data such as FPCB / PCB single board and panel feeding pad offset, board deformation, and board expansion and contraction to realize the calibration of dispensing machine dispensing path or dispensing coordinates. The F data stream is the PCB splitter calibration data stream. It combines the board position and deformation data of the FPCB / PCB single board and panel feeding to realize the calibration of the PCB splitter cutting path or cutting coordinates. The G data stream is the SPI-printer closed-loop data stream, used to correct deviations in the printing press itself, including alignment error, squeegee pressure, angle, and one of the demolding parameters. The H data stream is the closed-loop data stream for AOI-pick-place machine, used to correct the machine's own errors, including placement errors or nozzle errors.

4. The manufacturing method for multi-device interaction in an SMT production line according to claim 3, characterized in that, Based on the aforementioned basic measurement data, detection data, and / or the process data stream, multiple process deviations are identified, and the corresponding process data stream is corrected based on the process deviations, including: Based on the coordinate data in the basic measurement data, the pad offset and board deformation are statistically analyzed according to the unique number of the circuit board to generate a first process deviation. The first process deviation is used to correct the A data stream in order to adjust the board splitting process.

5. The manufacturing method for multi-device interaction in an SMT production line according to claim 3, characterized in that, Based on the detection data and the process data stream, multiple process deviations are identified, and the corresponding process data stream is corrected based on the process deviations, including: A second process deviation is generated based on the full pad coordinates confirmed by the unique circuit board number in the basic measurement data and the preset Gerber file. The second process deviation is used to correct the B data stream in order to adjust the alignment accuracy of the printing press.

6. The manufacturing method for multi-device interaction in an SMT production line according to claim 3, characterized in that, Based on the aforementioned basic measurement data, detection data, and / or the process data stream, multiple process deviations are identified, and the corresponding process data stream is corrected based on the process deviations, including: A third process deviation is generated based on the solder paste detection data and the basic measurement data in the detection data. The third process deviation is used to correct the G data stream in order to separate the inherent deviation of the printer and adjust the alignment accuracy of the printer.

7. The manufacturing method for multi-device interaction in an SMT production line according to claim 3, characterized in that, Based on the aforementioned basic measurement data, detection data, and / or the process data stream, multiple process deviations are identified, and the corresponding process data stream is corrected based on the process deviations, including: Solder paste printing or solder spraying is performed on the circuit board according to the C data stream; Solder paste inspection is performed on the circuit board based on the D data stream to obtain solder paste inspection data; The mounting offset parameters are confirmed based on the solder paste detection data, component type, and pad position. Based on the component types and pad positions in the basic measurement data, confirm the placement correction parameters, and generate the composite placement coordinates by combining the D data stream; The circuit board is subjected to pre-reflow surface inspection based on the D data stream to obtain placement deviation data. A fourth process deviation is generated based on the mounting deviation data and the basic measurement data. The fourth process deviation is used to correct the H data stream to improve the alignment accuracy of the pick-and-place machine.

8. A manufacturing apparatus for multi-device interaction in an SMT production line, characterized in that, include: The data processing module is used to receive basic measurement data of the original circuit board collected online or offline by a precision measuring machine, and generate corresponding process scheduling instructions and process data streams according to the preset process and the basic measurement data. The format unification module is used to convert heterogeneous data received by the data center into a standard format. The heterogeneous data includes at least basic measurement data, detection data, and process data streams. The data distribution module uploads the standardized basic measurement data, detection data, and process data stream to the data center. The data center stores, updates, and distributes the process data stream according to the process scheduling instructions. The process execution module is used to execute the circuit board manufacturing process according to the distributed process scheduling instructions and process data stream; The process inspection module is used to inspect the circuit board after the corresponding manufacturing process is executed in order to generate inspection data; The fusion analysis module is used to identify multiple process deviations based on the basic measurement data, detection data, and / or the process data stream, and to correct the corresponding process data stream based on the process deviations; the control process equipment is used to achieve full-line collaborative accuracy compensation based on the corrected process data stream.

9. A manufacturing system for multi-device interaction in an SMT production line, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the manufacturing method for multi-device interaction in an SMT production line as described in any one of claims 1-7.

10. A storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the manufacturing method for multi-device interaction in an SMT production line as described in any one of claims 1-7.

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