Patch production status visual display method, device, equipment and medium
By acquiring and analyzing equipment operation data from the SMT assembly line, the system automatically detects anomalies and provides visual information, solving the problem of low efficiency in manual monitoring. This enables real-time monitoring of the production line and optimization of equipment status, thereby improving production efficiency and fault response capabilities.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HEG OEM ELECTRONIC CO LTD
- Filing Date
- 2023-07-07
- Publication Date
- 2026-07-21
AI Technical Summary
In SMT assembly lines, existing technologies rely on manual monitoring, resulting in low production efficiency, an inability to obtain real-time information on production line operation, high labor costs, and difficulty in quickly identifying and maintaining equipment malfunctions.
By acquiring operational data from production equipment, anomaly prediction and visualization analysis can be performed, equipment status can be automatically detected, and visual information can be provided to quickly identify and maintain faulty equipment, thereby optimizing maintenance time and efficiency.
It enables real-time monitoring of the production line and rapid fault detection, reduces labor costs, improves production efficiency, reduces the possibility of equipment failure, and optimizes equipment maintenance strategies.
Smart Images
Figure CN116963492B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of SMT (Surface Mount Technology) manufacturing, and in particular to a method, apparatus, equipment, and medium for visualizing the manufacturing status of SMT production. Background Technology
[0002] Surface Mount Technology (SMT) is a key technology in the electronics manufacturing industry. SMT technology refers to the direct soldering of surface-mount electronic components onto the surface of a printed circuit board (PCB). Unlike traditional through-hole mounting processes, components and solder joints on an SMT PCB are all on the same surface. With the rapid development of the electronics and information industry, SMT technology has become an indispensable part of electronic assembly technology.
[0003] In the current SMT (Surface Mount Technology) production line environment, multiple pick-and-place machines operate simultaneously during the placement process, each placing different components. Each production line involves multiple steps, and an error or malfunction in any step can cause the entire production line to halt. Currently, technical personnel are responsible for monitoring the production line, manually monitoring the operation of each piece of equipment at regular intervals. This is not only time-consuming and labor-intensive but also inefficient, hindering managers from constantly monitoring production line efficiency and providing a direct view of the overall SMT production line's operation. Real-time monitoring of production status and equipment efficiency is also difficult. Summary of the Invention
[0004] To improve production efficiency and reduce labor costs, this application provides a method, apparatus, equipment, and medium for visually displaying the status of patch manufacturing.
[0005] Firstly, this application provides a method for visually displaying the status of patch manufacturing, employing the following technical solution:
[0006] A method for visually displaying the status of patch manufacturing includes:
[0007] Obtain operational data from each production equipment on the production line;
[0008] Anomaly prediction is performed based on the operational data to obtain the prediction results;
[0009] Visual analysis is performed based on the prediction results to obtain visual information.
[0010] The visualization information is used to monitor and display each piece of equipment on the production line.
[0011] By adopting the above technical solution, the production status of the SMT assembly line is collected and processed. Through monitoring the operating status of each piece of production equipment, when a malfunction occurs, anomaly detection can be performed using operational data, automatically determining the operating status of the equipment. If a malfunction occurs, not only can anomalies be automatically detected, but also visual information can help staff quickly locate the problem, enabling rapid maintenance and reducing the likelihood of equipment failures, thus increasing production efficiency. Simultaneously, the automatic detection of the equipment's operating status provides visualized monitoring of the assembly line production process, reducing labor costs. Operators can intuitively see the operating status of the entire production line and the individual equipment on it, enabling real-time monitoring of production line efficiency, fault data, and estimated maintenance times.
[0012] Preferably, the step of performing anomaly prediction based on the operational data to obtain the prediction result includes:
[0013] The placement efficiency of each first pick-and-place machine is obtained based on the operating data, where the placement efficiency is the time taken by the pick-and-place machine to process the PCB board;
[0014] Obtain the inventory quantity of the second pick-and-place machine, which is the current pick-and-place machine;
[0015] The placement time of the second placement machine is determined based on the placement efficiency and the inventory quantity;
[0016] Determine whether the patch application time is within a preset abnormal range;
[0017] If the patching time is within a preset abnormal range, an abnormal message is issued and the abnormal message is used as the prediction result.
[0018] By adopting the above technical solution, it is determined from the operating data whether the placement time of the second placement machine is within the preset abnormal range. If it is within the preset abnormal range, an abnormal information is issued and used as a prediction result. This reduces the occurrence of production line downtime caused by material shortage of the second placement machine, which leads to a decrease in production line efficiency and effectively improves the production line efficiency.
[0019] Preferably, after obtaining the placement efficiency of each pick-and-place machine based on the operating data, the method further includes:
[0020] Obtain the first maintenance time, which is the maintenance time of the last time the pick-and-place machine was maintained;
[0021] The second maintenance time is determined based on the preset maintenance cycle and the first maintenance time, and the second maintenance time is the next maintenance time of the pick-and-place machine;
[0022] The second repair time is adjusted based on the patching efficiency to obtain the final repair time.
[0023] By adopting the above technical solution, the second pick-and-place machine can be inspected at the final maintenance time. The maintenance time can be planned according to the actual situation, which reduces the occurrence of failure to clear faults and damages of the second pick-and-place machine in time due to the fixed preset maintenance cycle, and the occurrence of component damage and reduced production efficiency caused by long-term operation.
[0024] Preferably, the step of correcting the second repair time based on the patching efficiency to obtain the final repair time includes:
[0025] The efficiency difference is determined based on the patch efficiency and the preset patch efficiency;
[0026] Determine whether the efficiency difference is within a preset tolerance range;
[0027] If the efficiency difference is within a preset tolerance range, then the second maintenance time will be taken as the final maintenance time.
[0028] If the efficiency difference is not within the preset tolerance range, the maintenance level of the production equipment is determined based on the efficiency difference.
[0029] The second maintenance time is adjusted based on the maintenance level of the production equipment to obtain the third maintenance time;
[0030] The third maintenance time shall be taken as the final maintenance time.
[0031] By adopting the above technical solution, the maintenance level is determined based on the placement efficiency, and the second maintenance time is adjusted to obtain the third maintenance time, which is the final maintenance time. This reduces the occurrence of a decrease in placement efficiency caused by excessive running time of the second placement machine, and improves the production efficiency of the production line.
[0032] Preferably, determining the maintenance level of production equipment based on efficiency differences includes:
[0033] Obtain the placement type of the second pick-and-place machine;
[0034] The efficiency range of the production equipment is determined based on the patch type.
[0035] The maintenance level of each of the production equipment is determined based on the efficiency range and the efficiency difference, and the production equipment includes capacitor placement machines, resistor placement machines and chip placement machines.
[0036] Assign maintenance weights to the production equipment maintenance levels of the capacitor chip mounter, resistor chip mounter, and chip chip mounter.
[0037] The maintenance level of production line equipment is determined based on multiple maintenance weights.
[0038] By adopting the above technical solutions, the second maintenance time can be corrected more scientifically, making the final maintenance time more accurate, reducing the occurrence of production line efficiency decline due to overly intensive maintenance, and improving the production efficiency of the production line.
[0039] Preferably, after determining the maintenance level of the production equipment, the method includes:
[0040] The execution strategy is determined based on the maintenance level of the production equipment.
[0041] The sampling frequency is determined based on the execution strategy.
[0042] The PCB boards are randomly inspected according to the aforementioned inspection frequency;
[0043] AOI inspection of PCB boards is performed based on the sampling frequency to determine the defect types of the PCB boards.
[0044] By adopting the above technical solution, AOI inspection of PCB boards is performed based on the execution strategy, which reduces the number of PCB boards inspected by the AOI inspection machine and improves the inspection efficiency.
[0045] Preferably, the visualization analysis based on the prediction results to obtain visualization information includes:
[0046] Get a visualization template;
[0047] The visualization template is populated based on the prediction results to obtain a visualization report;
[0048] The visualization report is parsed to obtain the parsing results;
[0049] Based on the analysis results, a visualization method is selected, and the visualization method is used as the visualization information.
[0050] By adopting the above technical solution, the operating information and prediction results of the production equipment on the production line are analyzed, so that the operating information and prediction results of the production equipment on the production line can be displayed to the operators in a visual way. The operators can intuitively obtain the status information of the production line and monitor the production line in real time.
[0051] Secondly, this application provides a visualization display device for the chip assembly production status, which adopts the following technical solution:
[0052] A visualization device for displaying the status of patch manufacturing includes:
[0053] The acquisition module is used to acquire the operating data of each production equipment on the production line.
[0054] An anomaly prediction module is used to predict anomalies based on the operational data and obtain prediction results.
[0055] The visualization analysis module is used to perform visualization analysis based on the prediction results to obtain visualization information.
[0056] The monitoring and display module is used to monitor and display each piece of equipment on the production line based on the visualization information.
[0057] By adopting the above technical solution, the production status of the SMT assembly line is collected and processed. Through monitoring the operating status of each production device, when a fault occurs, abnormality detection can be performed using operating data, automatically determining the operating status of the production equipment. If a fault occurs, not only can abnormalities be automatically detected, but also visual information can help staff quickly locate the problem, enabling rapid maintenance and reducing the likelihood of equipment failure, thus increasing production efficiency. Simultaneously, the automatic detection of the production equipment's operating status provides visualized monitoring of the assembly production status, reducing labor costs. Operators can intuitively see the operating status of the entire production line and the operating status of each device on the line, enabling real-time monitoring of production line efficiency, fault data, and estimated maintenance time. Thirdly, this application provides an electronic device using the following technical solution:
[0058] An electronic device includes a memory and a processor, wherein the processor is coupled to the memory;
[0059] The memory stores a computer program that can be loaded by a processor and executed as described in any of the first aspects, a method for visualizing the status of patch manufacturing.
[0060] Fourthly, this application provides a computer-readable storage medium, which adopts the following technical solution:
[0061] A computer-readable storage medium storing a computer program capable of being loaded by a processor and executed as described in any of the first aspects, a method for visualizing the status of patch manufacturing. Attached Figure Description
[0062] Figure 1 This is a flowchart illustrating a method for visually displaying the status of patch manufacturing provided in an embodiment of this application.
[0063] Figure 2 This is a schematic diagram of the structure of a device for visualizing the status of patch manufacturing provided in an embodiment of this application.
[0064] Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Implementation
[0065] The present application will be further described in detail below with reference to the accompanying drawings.
[0066] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0067] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.
[0068] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.
[0069] This application provides a method for visually displaying the status of surface mount technology (SMT) production. This method can be executed by an electronic device, which can be a server or a terminal device. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet computer, desktop computer, etc., but is not limited to these.
[0070] This embodiment discloses a method for visually displaying the status of patch manufacturing. For example... Figure 1 As shown, the main process of the method for visualizing the chip assembly production status is described below (steps S101 to S104):
[0071] Step S101: Obtain the operating data of each production equipment on the production line.
[0072] When performing PCB board assembly, multiple production equipment are usually required to work together, such as pick-and-place machines, AOI inspection machines, and reflow ovens. These production equipment are connected through the Internet of Things (IoT) so that a central controller can acquire the operating data of each device.
[0073] The operational data includes the placement efficiency and running time of the pick-and-place machine, the number of PCBs inspected by the AOI inspection machine, and the inspection results; the pick-and-place machine includes at least one of the following: capacitor pick-and-place machine, resistor pick-and-place machine, and chip pick-and-place machine.
[0074] Step S102: Perform anomaly prediction based on the running data to obtain the prediction result.
[0075] Specifically, anomaly prediction is performed based on operational data, and the prediction results include: obtaining the placement efficiency of each first pick-and-place machine based on the operational data, where the placement efficiency is the time taken by the pick-and-place machine to process the PCB board; obtaining the inventory quantity of the second pick-and-place machine, where the second pick-and-place machine is the current pick-and-place machine; determining the placement time of the second pick-and-place machine based on the placement efficiency and inventory quantity; determining whether the placement time is within a preset anomaly range; if the placement time is within the preset anomaly range, issuing an anomaly message and using the anomaly message as the prediction result.
[0076] During the placement process, it is necessary to obtain the placement efficiency of the first placement machine and the inventory quantity in the second placement machine based on the operating data of each first placement machine. The first placement machine refers to all placement machines in the production line that place the same type of components on the PCB board, and the second placement machine is the placement machine to be predicted.
[0077] The inventory quantity is the remaining quantity of components in the second pick-and-place machine. After obtaining the inventory quantity of the second pick-and-place machine, the placement time of the second pick-and-place machine is determined based on the placement efficiency of the second pick-and-place machine and the inventory quantity. The placement time is the time during which the components in the second pick-and-place machine can be supplied for normal placement by the second pick-and-place machine.
[0078] When the placement time falls within a preset abnormal range, it indicates that the number of components remaining in the second placement machine is too low, and it will soon be unable to supply components for normal placement. The second placement machine will issue an abnormal message, including material level abnormality and placement efficiency abnormality. Material level abnormality occurs when the inventory quantity of the second placement machine is less than the minimum material level threshold, and placement efficiency abnormality occurs when the placement time based on the current inventory quantity is less than the minimum time threshold. When either material level abnormality or placement efficiency abnormality occurs, the operator is reminded to replenish materials promptly. The occurrence of both material level abnormality and / or placement efficiency abnormality indicates an abnormality in the second placement machine, and this abnormality is treated as a predicted outcome.
[0079] When the production line includes at least two of the above three types of pick-and-place machines, obtain the number of each type of pick-and-place machine, then obtain the inventory quantity and placement efficiency of each pick-and-place machine. Based on the inventory quantity and placement efficiency of each pick-and-place machine, determine whether each pick-and-place machine is abnormal. If a pick-and-place machine is abnormal, obtain the type of pick-and-place machine with the abnormality and the time it can perform placement. When the inventory quantity of the pick-and-place machine with the abnormality is 0, obtain other pick-and-place machines of the same type based on the type of pick-and-place machine with the abnormality, control the other pick-and-place machines of the same type to complete the placement task of the pick-and-place machine with the abnormality, and issue an abnormality information of material shortage.
[0080] If there are no other pick-and-place machines of the same type as the one that malfunctioned, the transport equipment in the production line will stop operating when it reaches the location of the malfunctioning pick-and-place machine, while the production equipment before the malfunctioning pick-and-place machine will continue to operate normally.
[0081] By taking the start time of placement on two adjacent PCBs of the second pick-and-place machine, the time taken for the second pick-and-place machine to process one PCB can be obtained. This time is the current placement efficiency of the second pick-and-place machine. The number of components consumed by the second pick-and-place machine for placing PCBs is a predetermined preset value depending on the task. The initial inventory of the second pick-and-place machine is a preset value entered by the operator when loading the machine. The second pick-and-place machine has a counter; after processing each PCB, the inventory is adjusted based on the number of components consumed, resulting in the current inventory of the second pick-and-place machine.
[0082] In this embodiment, we take a production line that includes only one type of chip mounter: resistor chip mounters.
[0083] The resistor placement machine consumes 10 resistors per PCB board. The machine's two most recent placement start times were 12:30:00 and 12:30:30, indicating a placement efficiency of 30 seconds. When loading, the machine had 600 remaining resistors. After processing 40 PCB boards, it consumed 400 resistors. Currently, it has 200 remaining resistors, and the placement time is 600 seconds, or 6 minutes. If the preset abnormal range is [0, 5) minutes, the placement time is outside this range, and the machine operates normally. If the preset abnormal range is [0, 10) minutes, the placement time is within this range, and an error message is issued.
[0084] Furthermore, after obtaining the placement efficiency of each pick-and-place machine based on the operating data, the method also includes: obtaining a first maintenance time, which is the maintenance time of the previous pick-and-place machine; determining a second maintenance time based on a preset maintenance cycle and the first maintenance time, which is the maintenance time of the next pick-and-place machine; and correcting the second maintenance time based on the placement efficiency to obtain the final maintenance time.
[0085] In this embodiment, after each pick-and-place machine has been running for a period of time, the internal components of the pick-and-place machine need to be inspected. When a problem is found in a component, the staff will repair or replace the component in a timely manner. After each repair or replacement, the time when the repair or replacement is completed is taken as the first repair time and recorded in the system of the pick-and-place machine, so that the staff or the central controller can obtain the first repair time at any time.
[0086] The preset maintenance cycle of the pick-and-place machine is determined based on its operating time. The preset maintenance cycle is related to the number of years the pick-and-place machine has been in use. Taking a resistor pick-and-place machine as an example: if the resistor pick-and-place machine has been in use for less than three years, the preset maintenance cycle should be once every 30 days; if the resistor pick-and-place machine has been in use for more than three years but less than five years, the preset maintenance cycle should be once every 25 days; and if the resistor pick-and-place machine has been in use for more than five years, the preset maintenance cycle should be once every 20 days.
[0087] The next maintenance time for the resistor placement machine can be obtained by calculating the preset maintenance cycle from the first maintenance time of the resistor placement machine; this is called the second maintenance time.
[0088] For example: If the maintenance time for the resistor placement machine is June 12th at 12:00, then the first maintenance time is June 12th at 12:00. If the resistor placement machine has been in use for 6 months, then the preset maintenance cycle is 30 days. Therefore, the expected next maintenance time for the resistor placement machine is July 12th at 12:00, and the second maintenance time is July 12th at 12:00.
[0089] Furthermore, the second maintenance time is corrected based on the placement efficiency to obtain the final maintenance time, which includes: determining the efficiency difference based on the placement efficiency and the preset placement efficiency; determining whether the efficiency difference is within the preset tolerance range; if the efficiency difference is within the preset tolerance range, then the second maintenance time is taken as the final maintenance time; if the efficiency difference is not within the preset tolerance range, then the maintenance level of the production equipment is determined based on the efficiency difference; the second maintenance time is corrected based on the maintenance level of the production equipment to obtain the third maintenance time; and the third maintenance time is taken as the final maintenance time.
[0090] The preset placement efficiency of a pick-and-place machine is the time it takes to process one PCB board under normal operation. In actual production, the preset placement efficiency is the time it takes to process the first PCB board after maintenance. The efficiency difference of the pick-and-place machine is the time difference obtained by calculating the difference between the placement efficiency of the pick-and-place machine and the preset placement efficiency.
[0091] In actual production, operators need to preset a tolerance range as a time range based on the actual production situation. In this embodiment, the preset tolerance time range is determined to be 5% or less of the efficiency difference compared to the placement efficiency.
[0092] In addition, when the efficiency difference is greater than 5% of the placement efficiency, the efficiency difference of the placement machine is not within the preset tolerance range. The maintenance level of the placement machine is determined according to the efficiency difference, including: when the efficiency difference is (5%, 10%) of the placement efficiency, the maintenance level is the first maintenance level; when the efficiency difference is (10%, 15%) of the placement efficiency, the maintenance level is the second maintenance level; and when the efficiency difference is greater than 15% of the placement efficiency, the maintenance level is the third maintenance level.
[0093] Taking a resistor placement machine as an example: the preset placement efficiency of the resistor placement machine is 20s, and the current placement efficiency of the resistor placement machine is 21s, then the efficiency difference of the resistor placement machine is 1s; 5% of the placement efficiency is 1s, so the preset tolerance range is that the efficiency difference is less than or equal to 1s; the resistor placement machine is within the tolerance range, and the final maintenance time is the second maintenance time.
[0094] When the efficiency difference of the resistor placement machine is (1s, 2s), the resistor placement machine is in the first maintenance level. When the resistor placement machine is in the first maintenance level, the second maintenance time is advanced by ten days to obtain the third maintenance time. If the current time is less than ten days away from the second maintenance time, the current time is the third maintenance time.
[0095] When the efficiency difference of the resistor placement machine is (2s, 3s), the resistor placement machine is in the second maintenance level. When the resistor placement machine is in the second maintenance level, the second maintenance time is advanced by 15 days to obtain the third maintenance time. If the current time is less than 15 days away from the second maintenance time, the current time is the third maintenance time.
[0096] When the efficiency difference of the resistor placement machine is greater than 3 seconds, the resistor placement machine is in the third maintenance level. When the resistor placement machine is in the third maintenance level, it is necessary to stop the operation of the resistor placement machine immediately and carry out maintenance. The current time is the third maintenance time.
[0097] The third maintenance time is the final maintenance time. When the current time equals the final maintenance time, the resistor placement machine is maintained.
[0098] The above are merely illustrative examples and are not intended to be limiting.
[0099] Furthermore, determining the maintenance level of production equipment based on efficiency differences includes: obtaining the placement type of the second pick-and-place machine; determining the efficiency range of the production equipment based on the placement type; determining the maintenance level of each piece of production equipment based on the efficiency range and efficiency differences, where the production equipment includes capacitor pick-and-place machines, resistor pick-and-place machines, and chip pick-and-place machines; assigning maintenance weights to the maintenance levels of the capacitor pick-and-place machines, resistor pick-and-place machines, and chip pick-and-place machines; and determining the maintenance level of the production line equipment based on multiple maintenance weights.
[0100] When a production line includes resistor placement machines, capacitor placement machines, and chip placement machines, their respective maintenance levels are determined. Then, weights are assigned based on the PCB processing time, with the machine taking the longest to process a PCB having the highest weight, the second longest having the second highest weight, and so on. Additionally, if there are multiple placement machines of a certain type on the production line, all of them have the same weight. The overall maintenance level of the production line equipment is determined by the sum of the products of each placement machine's maintenance level and its weight. For example:
[0101] The resistor placement machine takes the longest to process PCB boards, followed by the capacitor placement machine, and the chip placement machine takes the shortest time. Therefore, the weight of the resistor placement machine is 3, the weight of the capacitor placement machine is 2, and the weight of the chip placement machine is 1.
[0102] If the sum of the products of the maintenance level and weight of each pick-and-place machine is less than or equal to the critical value, the production line will continue maintenance without interruption. If the sum of the products of the maintenance level and weight of each pick-and-place machine is greater than the critical value, the production line will be shut down for maintenance. The critical value is the sum of the products of the maintenance level and weight of all pick-and-place machines on the production line when all machines are at the first maintenance level. For example:
[0103] The resistor placement machine is classified as the first maintenance level, the capacitor placement machine has no maintenance level, and the chip placement machine is classified as the second maintenance level. Therefore, the critical value is 6. The sum of the products of the maintenance level and weight of each placement machine production equipment is 5, and no line stoppage is required for maintenance.
[0104] Furthermore, after determining the maintenance level of the production equipment, the method includes: determining the execution strategy based on the maintenance level of the production equipment; determining the sampling frequency based on the execution strategy; sampling the PCB board according to the sampling frequency; and performing AOI inspection on the PCB board based on the sampling frequency to obtain the defect type of the PCB board.
[0105] Taking a resistor placement machine as an example: When the resistor placement machine is in the first maintenance level, the execution strategy is determined to be the first execution strategy. The first execution strategy includes sampling the total number of PCBs within a preset time. For example, if the total number of PCBs is 100 in 1 hour, 50 need to be sampled in this 1 hour. The sampling can be continuous or intermittent, and there is no limitation here.
[0106] When the resistor placement machine is in the second maintenance level, the execution strategy is determined to be the second execution strategy. The second execution strategy includes sampling the total number of PCBs within a preset time. For example, if the total number of PCBs is 100 in 1 hour, 80 need to be sampled in this 1 hour. The sampling can be continuous or intermittent, and there is no limitation here.
[0107] When the resistor placement machine is at the third maintenance level, the execution strategy is determined to be the third execution strategy, which includes inspecting the PCB board one by one.
[0108] PCB boards undergo AOI inspection. AOI inspection machines perform optical image inspection on PCB boards to check whether the appearance of the PCB board and its connected electronic components meets the requirements. By comparing with the standard appearance, PCB board defects are identified, including: the location of defective components on the PCB board, and the causes of the defects, such as solder bridging, short circuits, insufficient solder, and voids.
[0109] Step S103: Perform visualization analysis based on the prediction results to obtain visualization information.
[0110] In this embodiment, the central controller connects to each production device via the Internet of Things (IoT) to obtain the prediction results for each production device as data information to be visualized.
[0111] After acquiring the data information to be visualized, the data information is preprocessed to convert its data type into a form compatible with the data information of electronic devices. Specifically, the data information to be visualized is input into a preset preprocessing model, and then the data information to be visualized is output in a form compatible with the data information of electronic devices. The preset preprocessing model can be trained from historical data of different data types. The preprocessing model can be a neural network model, specifically a convolutional neural network model. Neural network models are a conventional technique and will not be elaborated on here.
[0112] Specifically, the visualization analysis based on the prediction results to obtain visualization information includes: obtaining a visualization template; populating the visualization template based on the prediction results to obtain a visualization report; parsing the visualization report to obtain the parsing results; and selecting a visualization display method based on the parsing results, using the visualization display method as the visualization information.
[0113] In this embodiment, the visualization template information includes at least one of the following: bar chart instruction, pie chart instruction, funnel chart instruction, scatter plot instruction, list instruction, stacked bar chart instruction, and side-by-side bar chart instruction. It also includes visualization template layout, visualization template theme color, and visualization template main style, but is not limited to these. A visualization report corresponding to the data information to be visualized is generated according to the selected visualization template generation rules. The visualization report is parsed to determine a suitable visualization display method for presenting the visualization information, which is then used as the visualization information.
[0114] Step S104: Monitor and display each piece of equipment on the production line based on the visualization information.
[0115] Visual information is displayed on the central controller's screen, allowing operators to monitor various devices on the production line.
[0116] Figure 2 This is a structural block diagram of a patch manufacturing status visualization device 200 provided in an embodiment of this application.
[0117] like Figure 2 As shown, a visualization display device 200 for patch manufacturing status mainly includes:
[0118] Module 201 is used to acquire the operating data of each piece of equipment on the production line;
[0119] Anomaly prediction module 202 is used to predict anomalies based on running data and obtain prediction results;
[0120] The visualization analysis module 203 is used to perform visualization analysis based on the prediction results and obtain visualization information.
[0121] The monitoring and display module 204 is used to monitor and display various equipment on the production line based on visual information.
[0122] As an optional implementation in this embodiment, the anomaly prediction module 202 is further specifically used to perform anomaly prediction based on operating data, and the prediction result includes: obtaining the placement efficiency of each first pick-and-place machine based on the operating data, where the placement efficiency is the time taken by the pick-and-place machine to process the PCB board; obtaining the inventory quantity of the second pick-and-place machine, where the second pick-and-place machine is the current pick-and-place machine; determining the placement time of the second pick-and-place machine based on the placement efficiency and inventory quantity; determining whether the placement time is within a preset anomaly range; if the placement time is within the preset anomaly range, issuing an anomaly message and using the anomaly message as the prediction result.
[0123] As an optional implementation in this embodiment, the anomaly prediction module 202 is further configured to, after obtaining the placement efficiency of each pick-and-place machine based on the operating data, include: obtaining a first maintenance time, the first maintenance time being the maintenance time of the previous pick-and-place machine; determining a second maintenance time based on a preset maintenance cycle and the first maintenance time, the second maintenance time being the maintenance time of the next pick-and-place machine; and correcting the second maintenance time based on the placement efficiency to obtain the final maintenance time.
[0124] As an optional implementation in this embodiment, the anomaly prediction module 202 is further specifically used to correct the second maintenance time based on the placement efficiency to obtain the final maintenance time, including: determining the efficiency difference based on the placement efficiency and the preset placement efficiency; determining whether the efficiency difference is within a preset tolerance range; if the efficiency difference is within the preset tolerance range, then using the second maintenance time as the final maintenance time; if the efficiency difference is not within the preset tolerance range, then determining the maintenance level of the production equipment based on the efficiency difference; correcting the second maintenance time based on the maintenance level of the production equipment to obtain a third maintenance time; and using the third maintenance time as the final maintenance time.
[0125] As an optional implementation in this embodiment, the anomaly prediction module 202 is further specifically used to determine the maintenance level of production equipment based on efficiency differences, including: obtaining the placement type of the second placement machine; determining the efficiency range of the production equipment based on the placement type; determining the maintenance level of each production equipment based on the efficiency range and efficiency differences, wherein the production equipment includes capacitor placement machines, resistor placement machines, and chip placement machines; assigning maintenance weights to the production equipment maintenance levels of capacitor placement machines, resistor placement machines, and chip placement machines; and determining the production line equipment maintenance level based on multiple maintenance weights.
[0126] As an optional implementation in this embodiment, the anomaly prediction module 202 is further specifically used to determine the maintenance level of the production equipment, and the method includes: determining an execution strategy based on the maintenance level of the production equipment; determining a sampling frequency based on the execution strategy; sampling the PCB board based on the sampling frequency; and performing AOI detection on the PCB board based on the sampling frequency to obtain the defect type of the PCB board.
[0127] As an optional implementation in this embodiment, the visualization analysis module 203 is also used to perform visualization analysis based on the prediction results to obtain visualization information, including: obtaining a visualization template; filling the visualization template based on the prediction results to obtain a visualization report; parsing the visualization report to obtain the parsing results; selecting a visualization display method based on the parsing results, and using the visualization display method as visualization information.
[0128] In one example, the module in any of the above devices may be one or more integrated circuits configured to implement the above methods, such as one or more application-specific integrated circuits (ASICs), or one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms.
[0129] For example, when modules in a device can be implemented via a processing element scheduler, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processor capable of calling programs. Alternatively, these modules can be integrated together as a system-on-a-chip (SOC).
[0130] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above-described device and module can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.
[0131] Figure 3 This is a structural block diagram of the electronic device 300 provided in an embodiment of this application.
[0132] like Figure 3 As shown, the electronic device 300 includes a processor 301 and a memory 302, and may further include one or more of an information input / output (I / O) interface 303, a communication component 304, and a communication bus 305.
[0133] The processor 301 controls the overall operation of the electronic device 300 to complete all or part of the steps of the above-described method for visualizing the status of surface mount production. The memory 302 stores various types of data to support the operation of the electronic device 300. This data may include, for example, instructions for any application or method operating on the electronic device 300, as well as application-related data. The memory 302 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as one or more of Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.
[0134] I / O interface 303 provides an interface between processor 301 and other interface modules, such as keyboards, mice, and buttons. These buttons can be virtual or physical. Communication component 304 is used for wired or wireless communication between electronic device 300 and other devices. Wireless communication includes Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, or 4G, or a combination thereof. Therefore, the corresponding communication component 304 may include a Wi-Fi component, a Bluetooth component, and an NFC component.
[0135] The electronic device 300 can be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to execute the surface mount production status visualization method given in the above embodiments.
[0136] The communication bus 305 may include a path for transmitting information between the aforementioned components. The communication bus 305 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus 305 may be divided into an address bus, a data bus, a control bus, etc.
[0137] Electronic device 300 may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers, and may also be servers.
[0138] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described method for visualizing the status of patch manufacturing.
[0139] The computer-readable storage medium may include various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0140] The terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.
[0141] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing application concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions claimed in this application.
Claims
1. A method for visually displaying the status of patch manufacturing, characterized in that, include: Obtain operational data from each production equipment on the production line; Anomaly prediction is performed based on the operational data to obtain the prediction results; Visual analysis is performed based on the prediction results to obtain visual information. The visualization information is used to monitor and display each piece of equipment on the production line. The anomaly prediction based on the operational data, and the resulting prediction, include: The placement efficiency of each first pick-and-place machine is obtained based on the operating data, where the placement efficiency is the time taken by the pick-and-place machine to process the PCB board; Obtain the inventory quantity of the second pick-and-place machine, which is the current pick-and-place machine; The placement time of the second placement machine is determined based on the placement efficiency and the inventory quantity; Determine whether the patch application time is within a preset abnormal range; If the patching time is within a preset abnormal range, an abnormal message is issued and the abnormal message is used as the prediction result. After obtaining the placement efficiency of each pick-and-place machine based on the operational data, the method further includes: Obtain the first maintenance time, which is the maintenance time of the last time the pick-and-place machine was maintained; The second maintenance time is determined based on the preset maintenance cycle and the first maintenance time, and the second maintenance time is the next maintenance time of the pick-and-place machine; The second repair time is corrected based on the patching efficiency to obtain the final repair time; The step of correcting the second repair time based on the patching efficiency to obtain the final repair time includes: The efficiency difference is determined based on the patch efficiency and the preset patch efficiency; Determine whether the efficiency difference is within a preset tolerance range; If the efficiency difference is within a preset tolerance range, then the second maintenance time will be taken as the final maintenance time. If the efficiency difference is not within the preset tolerance range, the maintenance level of the production equipment is determined based on the efficiency difference. The second maintenance time is adjusted based on the maintenance level of the production equipment to obtain the third maintenance time; The third maintenance time shall be taken as the final maintenance time; The method of determining the maintenance level of production equipment based on efficiency difference includes: Obtain the placement type of the second pick-and-place machine; The efficiency range of the production equipment is determined based on the patch type. The maintenance level of each of the production equipment is determined based on the efficiency range and the efficiency difference, and the production equipment includes capacitor placement machines, resistor placement machines and chip placement machines. Assign maintenance weights to the production equipment maintenance levels of the capacitor chip mounter, resistor chip mounter, and chip chip mounter. The maintenance level of production line equipment is determined based on multiple maintenance weights. After determining the maintenance level of the production equipment, the method further includes: The execution strategy is determined based on the maintenance level of the production equipment. The sampling frequency is determined based on the execution strategy. The PCB boards are randomly inspected according to the aforementioned inspection frequency; AOI inspection of PCB boards is performed based on the sampling frequency to determine the defect types of the PCB boards.
2. The method according to claim 1, characterized in that, The visualization analysis based on the prediction results to obtain the visualization information includes: Get a visualization template; The visualization template is populated based on the prediction results to obtain a visualization report; The visualization report is parsed to obtain the parsing results; Based on the analysis results, a visualization method is selected, and the visualization method is used as the visualization information.
3. A visualization device for displaying the status of patch manufacturing, characterized in that, For implementing the method as described in claim 1, including, The acquisition module is used to acquire the operating data of each piece of equipment on the production line. An anomaly prediction module is used to predict anomalies based on the operational data and obtain prediction results. The visualization analysis module is used to perform visualization analysis based on the prediction results to obtain visualization information. The monitoring and display module is used to monitor and display each piece of equipment on the production line based on the visualization information.
4. An electronic device, characterized in that, Includes a processor, which is coupled to a memory; The processor is configured to execute a computer program stored in the memory, such that the electronic device performs the method as described in any one of claims 1-2.
5. A computer-readable storage medium, characterized in that, Includes a computer program or instructions that, when run on a computer, cause the computer to perform the method as described in any one of claims 1-2.